Health content interaction methods, devices, electronic devices, storage media, and program products

Abstract

This disclosure provides a health content interaction method, device, electronic device, storage medium, and program product, which can be applied to the fields of artificial intelligence and medical health technology. The health content interaction method includes: responding to a user's request for consultation on the effects of a product, obtaining the target body part information of the user through an interactive interface; generating expected effect display content for the target body part based on the product information and body part information, wherein the expected effect display content presents the expected change process of the target body part under the action of the product; and displaying the expected effect display content to the target user through the interactive interface.

Description

Technical Field

[0001] This disclosure relates to the fields of artificial intelligence and healthcare technology, and more specifically, to a method, device, electronic device, storage medium, and program product for health content interaction. Background Technology

[0002] In the sales scenarios of fields such as healthcare and personal care, users generally have a strong expectation of the effects of using the product.

[0003] In related technologies, AI agents based on large language models (LLMs) typically provide services through text-based question answering and static product information cards. This approach can only provide users with relatively simple and rigid effect information, resulting in a lack of intuitive demonstration of the product's usage effects. Summary of the Invention

[0004] This disclosure provides a method, apparatus, electronic device, storage medium, and program product for interacting with health content.

[0005] According to one aspect of this disclosure, a method for interactive health content is provided, comprising: responding to a user's request for consultation on the effects of a product, obtaining part information of a target part of the user's body through an interactive interface; generating expected effect display content for the target part based on product information and the part information, wherein the expected effect display content presents the expected change process of the target part under the influence of the product; and displaying the expected effect display content to the target user through the interactive interface.

[0006] According to another aspect of this disclosure, a health content interactive device is provided, comprising: an acquisition module, configured to acquire, in response to a user's request for consultation on the effects of a product, part information of a target part of the user through an interactive interface; a generation module, configured to generate expected effect display content for the target part based on product information and the part information, wherein the expected effect display content presents the expected change process of the target part under the action of the product; and a display module, configured to display the expected effect display content to the target user through the interactive interface.

[0007] According to another aspect of this disclosure, an electronic device is provided, comprising: one or more processors; and a memory for storing one or more instructions, wherein, when executed by the one or more processors, the one or more processors cause the one or more processors to perform the method as described in this disclosure.

[0008] According to another aspect of this disclosure, a computer-readable storage medium is provided having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described in this disclosure.

[0009] According to another aspect of this disclosure, a computer program product is provided, which includes computer-executable instructions that, when executed, are used to perform the methods described in this disclosure. Attached Figure Description

[0010] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0011] Figure 1 This illustration schematically shows a system architecture to which a health content interaction method can be applied according to an embodiment of the present disclosure;

[0012] Figure 2 A flowchart illustrating a health content interaction method according to an embodiment of the present disclosure is shown schematically;

[0013] Figure 3A An example schematic diagram of an interactive interface according to an embodiment of the present disclosure is shown;

[0014] Figure 3B This illustration schematically shows an example of a process for obtaining location information of a target location of an object through an interactive interface according to an embodiment of the present disclosure;

[0015] Figure 4 The illustration shows an example diagram illustrating the process of generating expected effect display content for a target part based on product information and part information of a product, according to an embodiment of the present disclosure.

[0016] Figure 5A This illustration shows an example diagram of displaying a set of phased static information to a target object through an interactive interface according to an embodiment of the present disclosure;

[0017] Figure 5B This illustration shows an example diagram of displaying dynamic interactive video to a target object through an interactive interface according to an embodiment of the present disclosure;

[0018] Figure 6A The illustration shows an example diagram of a triggering operation process for a product transaction address according to an embodiment of the present disclosure;

[0019] Figure 6B This illustration schematically shows an example diagram of a product transaction interface corresponding to a product transaction address, according to an embodiment of the present disclosure.

[0020] Figure 7A block diagram of a health content interaction device according to an embodiment of the present disclosure is schematically shown; and

[0021] Figure 8 A block diagram of an electronic device suitable for implementing a health content interaction method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0022] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0023] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0024] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0025] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0026] In the technical solution of this invention, the user information (including but not limited to user personal information, user image information, user device information, such as location information) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of related data all comply with relevant laws, regulations, and standards, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entry points for users to choose to authorize or refuse.

[0027] In the sales scenarios of fields such as healthcare and personal care, users generally have a strong expectation and demand for the effects of using the product.

[0028] In related technologies, it is common to rely on AI agents based on large language models to provide services through methods such as text-based question answering and static product information cards.

[0029] However, this plain text combined with pre-set content mode has significant drawbacks: First, it lacks an intuitive and visual demonstration of personalized effects. For example, when users consult about scar removal cream, they can only obtain general text descriptions or standard diagrams provided by manufacturers, and cannot obtain a tailored effect simulation based on the specific shape, color, formation time, and cause of their own scars. Second, this display method is static and lacks process, making it difficult for users to perceive the dynamic and continuous recovery process from the current state to the improvement goal. This leads to a cognitive blind spot for users when making decisions, affecting their purchase confidence and experience.

[0030] To this end, this disclosure provides a health content interaction method, device, electronic device, storage medium, and program product, which can be applied to the fields of artificial intelligence, large-scale models, and human-computer interaction. The health content interaction method includes: responding to a user's request for information on the effects of a product, obtaining the target body part information of the user through an interactive interface; generating expected effect display content for the target body part based on the product information and body part information, wherein the expected effect display content presents the expected change process of the target body part under the influence of the product; and displaying the expected effect display content to the target user through the interactive interface.

[0031] Figure 1 The illustration schematically depicts a system architecture to which a health content interaction method can be applied according to embodiments of this disclosure. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0032] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between different devices.

[0033] It should be noted that the health content interaction method provided in this disclosure embodiment can generally be executed by server 105. Accordingly, the health content interaction device provided in this disclosure embodiment can generally be set in server 105.

[0034] Alternatively, the health content interaction method provided in this embodiment of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the health content interaction device provided in this embodiment of the present disclosure can also be disposed in the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0035] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0036] It should be noted that the sequence numbers of the operations in the following methods are for descriptive purposes only and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.

[0037] The foregoing has described the system architecture for applying the health content interaction method provided in this disclosure. The following will use... Figure 2 The following example further illustrates the content interaction process of this disclosure.

[0038] Figure 2 A flowchart illustrating a health content interaction method according to an embodiment of the present disclosure is shown schematically.

[0039] like Figure 2 As shown, the health content interaction method 200 includes operations S210~S230.

[0040] In operation S210, in response to an object's inquiry about the product's effectiveness, the part information of the target part of the object is obtained through the interactive interface.

[0041] When operating S220, based on the product information and part information, the expected effect display content for the target part is generated. The expected effect display content presents the expected change process of the target part under the action of the product.

[0042] When operating S230, the expected display content is presented to the target object through the interactive interface.

[0043] The target audience is the individual requesting consultation on the desired effects. The product is a product with expected effects that need to be visually perceived. The target area is the part of the body on which the product is expected to act on the target audience. For example, the target audience could be a user who wants to remove scars, the product could be a scar removal cream, and the target area could be the scarred area on the user's face; alternatively, the target audience could be a user who wants to buy a face mask, the product could be a face mask, and the target area could be a skin area, etc., without limitation.

[0044] Product information can include the product's attributes, ingredients, and mechanisms of action. Target area information can include descriptive and visual information. For example, descriptive information can be obtained through interactive Q&A, and may include the cause and timing of the target area's formation. Visual information can include images or videos of the target area, such as user-uploaded scar images.

[0045] The method for initiating an effectiveness consultation request can be configured according to actual business needs and is not limited here. For example, the interactive interface can provide a button for initiating an effectiveness consultation request, which the user can click to initiate the request; alternatively, the user can initiate an effectiveness consultation request via voice command, etc.

[0046] After receiving a request for feedback, the server can obtain the target body part information of the user through an interactive interface. For example, it can use an LLM-based agent to conduct multi-turn dialogues to collect text information and receive uploaded images / videos as body part information. Alternatively, a structured form or questionnaire interface can be provided, allowing users to directly select or fill in fields to obtain body part information. Another option is to guide the user to scan the target body part in real-time using their device's camera through an AR interface, supplementing the information with key contextual information such as voice or simplified options.

[0047] In one embodiment, the target area may include a scar, and the product may include an article for repairing the scar. For example, the product may include topical scar creams, topical scar gels, scar patches, silicone patches, medical scar care ointments, and other medical dressings or skin care products with repairing effects.

[0048] When the target site is a scar, the site information may include at least one of the following: formation time and cause. Additionally, the site information may include a scar image, the image features of which may include at least one of the following: area extent, color features, and depth features.

[0049] Formation time refers to the length of time that has elapsed from the formation of the target area to the present moment. For example, formation time can be "3 months", "1 year", "more than 5 years", etc. The cause of formation refers to the original event or pathological process that led to the formation of the target area. Scars with different causes may have different histological characteristics and repair responses. For example, formation time can be "surgical incision", "burn", "acne (pimples)", "traumatic bumps and knocks", "vaccination", etc., and is not limited here.

[0050] The formation time and cause mentioned above can be obtained through multi-turn dialogue by the intelligent agent, actively asking and extracting information such as "How did your scar get there?" and "Approximately how long has it been there?" Alternatively, the interface can provide a drop-down selection box for the cause and a date selector or duration input box for the formation time, allowing the user to directly select or input information. Alternatively, with the subject's authorization, relevant surgical history, trauma history, and time information can be automatically obtained from the subject's Electronic Health Record (EHR) or past consultation records.

[0051] The region extent refers to the size and shape of the space occupied by the target area in the image. For example, the region extent can be the area of ​​the scar pixel region obtained by image segmentation, or the length and width of its outer rectangle. Color features refer to the color attributes of the target area in the image. For example, color features can be the average RGB value of the scar area, the hue (H) and saturation (S) in the HSV space, and the color contrast with the surrounding normal skin, which are not limited here.

[0052] Depth features refer to the degree of elevation or depression of a target area relative to the surrounding normal skin surface. They can be used to distinguish between raised and depressed scars. For example, depth features can be obtained by estimating the average height or depth of the scar through binocular vision, structured light, or shadow analysis, or by determining the levels of "raised", "flat", or "depressed" by a classification model. No specific limit is imposed here.

[0053] In the embodiments of this disclosure, by limiting the target area to scars and the product to items used for scar repair, the problem addressed by this solution is the user's need for predicting the scar repair effect in fields such as medical devices or skin care product sales guides. This allows subsequent information processing, knowledge base retrieval, and effect generation to be optimized around the patterns and visual characteristics of scar repair, thereby ensuring the accuracy of the predicted scar repair effect and the final expected effect display content in the scenario of predicting the scar repair effect.

[0054] In the embodiments of this disclosure, since the formation time and cause of scars are key factors affecting the difficulty, cycle and expected effect of their repair, and this information is difficult to obtain directly from the site image, by limiting the site information to include at least one of the formation time and cause, it is possible to call on the corresponding professional knowledge to perform differentiated stage division and effect inference based on scars with different times and causes, thereby enhancing the medical rationality and accuracy of personalized prediction.

[0055] Furthermore, since the area range, color features, and depth features are objective quantitative descriptions of the visual state of scars, automatically identifying and extracting these key features from the site images provides accurate and calculable visual change anchors for subsequent effect simulation, thereby making the generated simulation images at each stage more realistic and credible in terms of the evolution of key visual indicators.

[0056] After obtaining product and site information through the interactive interface, the system can generate content showcasing the expected effects on the target site. This content presents the anticipated changes in the target site under the product's influence, showing the expected continuous or phased evolution of the site's state over time. For example, if the target site is a scar, the content could include a series of simulated images or videos demonstrating the scar's transformation from its current state, through initial improvement, intermediate fading, and eventual healing after product use.

[0057] The method for generating the expected display content can be configured according to actual business needs and is not limited here. For example, a text generation model can be used to process product and part information to obtain a stage description, which can then drive a text-to-image model to generate the expected display content. Alternatively, based on the part information of the target part and product information, an image-to-image diffusion model or a Generative Adversarial Network (GAN) model can be directly used to generate the expected display content by adjusting parameters such as representation time or effect intensity.

[0058] After obtaining the desired effect display content, it can be shown to the target audience through an interactive interface. For example, the desired effect display content can be shown directly in the display area of ​​the interactive interface. Alternatively, AR technology can be used to overlay the desired effect as an overlay onto the real target area seen by the user through the camera in real time. Another option is to generate a downloadable report or link containing detailed stage descriptions, effect comparison images, and precautions, and push it to the target audience via email or message.

[0059] In the embodiments of this disclosure, personalized, multi-dimensional current status data of the target user is actively collected by responding to effect consultation requests and obtaining part information. Expected effect display content is generated based on product information and part information, integrating specific product attributes with individual user characteristics. This achieves personalized and professional customization of effect prediction, making the generated expected effect display content highly relevant to the user's own situation. Based on this, by presenting the aforementioned personalized and professional expected change process to the target user intuitively and dynamically, it at least partially overcomes the technical problem in related technologies of lacking personalized, phased, and interactive intuitive displays of product usage effects in shopping guide scenarios. This provides the target user with a visual and perceptible interactive shopping guide experience, thereby improving the target user's clarity and accuracy of understanding product usage effects.

[0060] According to an embodiment of this disclosure, operation S210 may include the following operations: in response to an effect consultation request, the agent engages in multiple rounds of interactive dialogue with the object through an interactive interface to guide the object to input information about the target body part; and the body part information is determined based on the dialogue information obtained through the multiple rounds of interactive dialogue.

[0061] An intelligent agent is a virtual assistant built on a large language model or other dialogue AI technology, capable of understanding natural language and engaging in continuous dialogue. In embodiments of this disclosure, the intelligent agent may be a dialogue program possessing specific domain knowledge, such as an AI pharmacist or an AI nutritionist.

[0062] In response to requests for feedback on effectiveness, the agent can engage in multiple consecutive question-and-answer sessions or information exchanges with the user to gradually and systematically guide the user to provide complete information. For example, during this process, the agent can proactively ask questions, clarify doubts, and provide options to encourage or assist the user in providing an effective description of the target area.

[0063] The interactive interface provides a button for initiating an effectiveness consultation request, which the user clicks to do so. Upon receiving the request, the intelligent agent can first greet the user and inquire about their core needs. Then, based on the initial response, it can ask follow-up questions like a real expert. For example, the agent might ask, "How did this scar get there?" The user might reply, "Surgery a year ago." The agent could then ask, "Is the scar now noticeably raised or very dark? Could you please take a clear photo and upload it?" Through this multi-round, logical dialogue, the agent naturally guides the user to gradually provide more information about the affected area.

[0064] The questioning methods of the intelligent agent can be configured according to actual business needs and are not limited here. For example, an intelligent agent based on LLM can conduct open-domain dialogue, dynamically generating subsequent questions using its context understanding capabilities. Alternatively, the intelligent agent can select the next most appropriate question from a predefined question-and-answer flowchart based on the user's current answer. The intelligent agent can also proactively provide options for the user to choose from.

[0065] Dialogue information is the collection of all text content generated throughout the multi-turn dialogue process. Dialogue information can include questions, prompts, and options issued by the agent, as well as responses, descriptions, and image upload commands input by the recipient. After obtaining the dialogue information, it can be used directly as part information; alternatively, part information required for generating subsequent effects can be extracted from the dialogue information.

[0066] In the embodiments of this disclosure, addressing the pain point that the subject may not be clear about what information needs to be provided, by utilizing multiple rounds of interaction between the intelligent agent and the subject to conduct multi-round, progressive questioning and interaction, it is possible to systematically guide the user to gradually supplement the various types of information necessary to complete the effect prediction, thereby lowering the threshold for the subject's expression. It can gradually guide the subject to input detailed information about the target area, avoiding prediction failures caused by incomplete or disordered user information input. Furthermore, by simulating the dialogue process of a professional consultation, it enhances the professionalism and credibility of the service while collecting information.

[0067] Based on this, by obtaining location information, key information can be automatically identified, extracted, and structured from lengthy natural language dialogue records, and then integrated to form usable location information. This overcomes the problem of information omissions or ambiguities that may result from simply relying on users to actively fill in standardized forms, thereby ensuring the completeness of information collection and improving the efficiency and accuracy of information acquisition.

[0068] The following will be based on Figure 3A and Figure 3B As an example, the process of obtaining the location information of the target part of an object through an interactive interface will be further explained in this disclosure.

[0069] Figure 3A An example schematic diagram of an interactive interface according to an embodiment of the present disclosure is shown.

[0070] like Figure 3A As shown, in embodiment 300A of the interactive interface, taking "XX Doctor" as an example, the interactive interface can provide an "Experience Now" button for product effect evaluation. The object can initiate an effect consultation request by clicking the button.

[0071] Figure 3BThe illustration shows an example diagram of a process for obtaining location information of a target part of an object through an interactive interface according to an embodiment of the present disclosure.

[0072] like Figure 3B As shown in embodiment 300B, which acquires site information, during multiple rounds of interactive dialogue, the agent can ask, "Scars formed after an abrasion require special care. What stage is your abrasion at now? Is it just scabbed over, has the scab just fallen off, or has a noticeable scar already formed?" The subject answers, "A noticeable scar has already formed." The agent can further ask, "I understand. Since the scar has formed, it is indeed necessary to continue using scar removal products to improve it. Can you describe the current appearance of this scar in detail? For example, is there any redness, raised area, or pigmentation?" The subject answers, "Redness, pigmentation, raised area," etc.

[0073] In addition, the intelligent agent can guide objects to upload images of body parts. For example, the interface can provide an "Upload Image" button, which objects can click to trigger the image upload process, thereby uploading images of body parts and improving the body part information.

[0074] According to an embodiment of this disclosure, operation S220 may include the following operations: generating effect description text for the change process based on product information and part information, wherein the effect description text is used to describe the expected state of the target part at each stage of the change process; generating simulated effect images for each stage based on the effect description text; and generating expected effect display content based on the simulated effect images for each stage.

[0075] Product information can include the product's inherent attributes and its mechanism of action. For example, if the product is a scar removal cream, the product information would include its core ingredients, applicable scar types, and mechanism of action. It should be noted that product information can be sourced from product databases or external medical knowledge bases.

[0076] After obtaining product and site information, effect description text can be generated to describe the changes. This effect description text can be structured, phased natural language descriptions used to define the expected state at each point in time or stage of the change process. For example, the effect description text could be: "After the first month of use, the redness of the scar has faded, and the height of the raised area has decreased by approximately 20%; after the third month of use, the color is close to the surrounding skin tone, and the texture has noticeably softened."

[0077] The specific method for generating the effect description text can be configured according to actual business needs and is not limited here. For example, a large language model can be used to call a structured knowledge base for reasoning to generate the effect description text. Alternatively, a rule base representing the correspondence between scar type, product ingredients, time, stage of effect, etc., can be predefined, and the effect description text can be generated through matching logic. Another option is to first retrieve the cases and their effect descriptions that are most similar to the current product and site information from a large number of clinical case literature, and then use this to guide the large language model to generate the effect description text.

[0078] After obtaining the effect description text, simulated effect images for each stage can be generated. The simulated effect images are visualizations generated based on the effect description text, reflecting the expected state of the target area at a specific stage.

[0079] The specific method for generating the simulated effect image can be configured according to actual business needs and is not limited here. For example, the effect description text can be input into the text-based image model to generate a simulated effect image that matches the description and evolves from the original part image. Alternatively, a text-based image diffusion model can be used, using the effect description text as prompts and the original part image as a reference to generate the simulated effect image.

[0080] After obtaining the simulated effect images for each stage, the expected effect display content can be generated. The expected effect display content is the final visual output form formed by integrating the simulated effect images from each stage. For example, the expected effect display content can be a poster containing a comparison chart of "current state - stage 1 - stage 2 - final effect", or it can be an interactive video that allows viewers to view continuous changes by dragging a slider, etc., without limitation.

[0081] In the embodiments of this disclosure, since the effect description text is generated based on product information and location information, it can combine specific product attributes with individualized location features of the object, integrating product characteristics with the user's specific scar information. This enables the generation of a phased expected state description that matches the user's individual situation and product mechanism, ensuring the personalization and logic of effect prediction. It also transforms product information and location information into accurate phased text descriptions, providing precise and reliable semantic guidance for subsequent visualization generation.

[0082] By generating simulated effect images for each stage based on the effect description text, a precise conversion from textual semantics to concrete visual imagery is achieved, making the abstract expected state intuitive and visible. This provides the object with a directly perceptible simulated effect image that is tied to its own situation, ensuring that the generated image not only reflects the expected effect inferred from professional knowledge, but also maintains consistency with the user's original situation in terms of visual style and conditions, thereby enhancing the credibility of the simulated effect and the user's sense of immersion.

[0083] Based on this, since the content displayed for the expected effect is generated from simulated effect images at each stage, a transformation from discrete, staged images to a complete and smooth demonstration of the change process is achieved. This fully presents the continuous process of effect change, allowing the expected evolution of the product's function to be presented to the user intuitively, vividly, and continuously. This improves the accuracy, personalization, and user experience of the effect display, thereby enhancing the efficiency of information delivery and the immersive experience of the user. According to embodiments of this disclosure, the part information may include a part image of the target part. The part image may be a digital image or video frame acquired through an image acquisition device, reflecting the current visual state of the target part. For example, the subject may use a photo of a facial scar taken and uploaded by a mobile phone camera.

[0084] For images of body parts, computer vision technology can be used to automatically detect, segment, and quantify their visual attributes to obtain image features that can digitally represent the visual state of the target body part. For example, image features may include appearance features, morphological features, and environmental features. Morphological features may include at least one of the following: region extent, perimeter, and boundary sharpness; appearance features may include at least one of the following: color features, texture features, and pigmentation level; and environmental features may include at least one of the following: illumination uniformity and shooting angle.

[0085] After obtaining image features, the image features, product information, and body part information can be input into the first large-scale model to generate descriptive text. The first large-scale model is a large pre-trained model capable of processing multimodal input and generating natural language. For example, image features, product information, and body part information can be encoded and concatenated to form a unified input sequence before being input into the first large-scale model.

[0086] Alternatively, image features and product information can be used as query criteria to retrieve the most similar reference cases and their effect descriptions from a structured medical effect case database. These search results are then used as context, along with the original input, and fed into a large language model to generate the final effect description text.

[0087] Alternatively, an effect framework template can be matched based on image features and product information. This effect framework template can be divided into anti-inflammatory period, repair period, stabilization period, etc. Then, the first model fills in and refines the detailed description of each stage according to the specific part information to generate effect description text.

[0088] In the embodiments of this disclosure, by performing feature recognition on the images of the affected parts, the intuitive visual information provided by the user can be transformed into an objective quantification of the individual's condition. Unstructured image data is transformed into structured feature information that can be understood and utilized by the model. This overcomes the problem that pure text descriptions or general schematic diagrams cannot accurately reflect the individual differences of users. It provides an objective and accurate visual data foundation for generating effect predictions that are highly tailored to the user's own condition. This ensures the personalization of the solution from the source and ensures the realism and credibility of the final display effect.

[0089] Building upon this foundation, by inputting image features, product information, and location information into the first large model, intuitive visual quantitative data, specific product attribute data, and user-supplemented contextual text data can be fused in a multimodal manner. This fully leverages the objectivity of visual information and the reasoning capabilities of the large model to scientifically analyze and describe in stages the expected changes of a specific product acting on a specific target location. As a result, the generated effect description text not only closely integrates the user's individual visual condition but also incorporates product expertise, thereby improving the accuracy, credibility, and personalization of effect prediction.

[0090] According to embodiments of this disclosure, before inputting image features, product information, and site information into the first large model, a stage division rule can be obtained by matching a reference knowledge base based on the target site type and the product's ingredients. The target site type can be obtained by classifying the target site based on medical or domain knowledge. For example, in a scar scenario, the target site type may include "hypertrophic scar," "atrophic scar," "keloid," "superficial scar," etc. The product's ingredients refer to the functional substances that play a major role in the product. For example, taking a scar removal cream as an example, the ingredients may include "silicone," "onion extract," "vitamin E," etc., found in scar removal creams.

[0091] The reference knowledge base can store the expected improvement features of multiple candidate components for multiple candidate site types at various stages. Specifically, it stores the correlations between the expected improvement features of a specific candidate component applied to a specific candidate site type over time. Expected improvement features can be descriptions of the expected changes in a specific dimension of the target site at a specific stage. For example, expected improvement features may include "color: from dark red to light pink," "texture: from hard to soft," and "height: from 1mm raised to flat."

[0092] For example, if a reference knowledge base stores candidate correspondences between candidate components, candidate types, and expected improvement features at each stage, then the target part type can be matched with the candidate types in each candidate correspondence in the reference knowledge base to obtain a filtered candidate correspondence. Then, based on the product's composition, the candidate components in each of these filtered candidate correspondences are matched to obtain the target correspondence. This target correspondence indicates the expected improvement features at each stage corresponding to the target part type and the product's composition.

[0093] The specific method for matching the reference knowledge base based on the target part type and product composition can be configured according to actual business needs and is not limited here. For example, the reference knowledge base can be precisely matched based on the target part type and product composition; alternatively, the composition and target part type can be represented as vectors, and the similarity between these vectors and the vectors of each entry in the reference knowledge base can be calculated.

[0094] The stage division rules are determined based on the expected improvement characteristics of each stage. The stage division rules can define the number of stages included in the change process and the expected improvement characteristics of each stage. For example, taking the target area type as "hypertrophic scar" and the product type as "silicone", the stage division rules for applying "silicone" to "hypertrophic scar" might be: "Number of stages: 3; Expected improvement characteristics of stage 1 (0-1 month): anti-inflammatory and redness reduction; Expected improvement characteristics of stage 2 (1-3 months): softening and flattening; Expected improvement characteristics of stage 3 (3-6 months): color fusion."

[0095] After obtaining the stage division rules, the stage division rules, image features, product information, and part information can be input into the first main model to obtain the effect description sub-texts for each stage. For example, all the above information can be input into the first main model to simultaneously obtain the effect description sub-texts for each stage. Alternatively, the effect description sub-text for the first stage can be generated first, and then the effect description sub-text for the second stage can be generated using the effect description sub-text for the first stage as new context, and so on, thus ensuring logical coherence between stages.

[0096] In the embodiments of this disclosure, by dividing the effect description text into multiple effect description sub-texts for each stage, the continuous and complex expected change process under the action of the product is decomposed into several discrete and logically progressive stage descriptions. This not only makes the final generated effect display content have a clear time evolution logic, making it easier for users to gradually understand the expected change process, but also provides accurate text references for the subsequent generation of images corresponding to each stage.

[0097] By introducing a reference knowledge base and matching the obtained stage division rules, and matching specific user body part types with specific product ingredients, the scientific stage division rules for that specific combination and the expected improvement characteristics of each stage can be automatically obtained. This ensures that the framework of the entire expected change process is built on verified professional medical knowledge, establishing a scientific and professional structured framework for the generation of effect description text, and ensuring the rationality and accuracy of stage division and its expected improvement characteristics.

[0098] Based on this, by using the first major model to reason about the stage division rules, image features, product information, and part information, the first major model, when generating descriptive text, is not only based on individualized image and contextual information, but is also directly guided and constrained by professional stage division rules. This ensures that the generated effect description sub-text for each stage can deeply integrate the user's personalized characteristics and product information while conforming to the professional stage division framework. As a result, it can generate effect description sub-texts for each stage that are both in line with professional consensus and highly personalized, ensuring high quality of generated content in both scientific and personalized dimensions.

[0099] According to embodiments of this disclosure, generating simulated effect images for each stage based on effect description text may include the following operations: adding effect description sub-texts for each of multiple stages to a prompt template to obtain prompt information, wherein the prompt template includes instructions for instructing the target part to be processed according to the effect description sub-texts of the stage; inputting part information and prompt information into a second large model to obtain simulated effect images for each stage.

[0100] The prompt template is a pre-defined text structure or framework that can be used to organize and format instructions input to the second-largest model. For example, the prompt template could be: "Please generate realistic images reflecting the expected effects of each stage based on the following part information and the effect description sub-texts for each stage. Part information: [Original description], Stage 1 ([Stage 1 time]): [Stage 1 effect description sub-text], Stage 2 ([Stage 2 time]): [Stage 2 effect description sub-text], Stage 3 ([Stage 3 time]): [Stage 3 effect description sub-text], please generate simulated effect images for each of the above three stages respectively."

[0101] The second major model is capable of generating or modifying images based on prompts. For example, the second major model can include text-to-image models and image-to-image models. For instance, the part information and prompts can be directly input into the second major model to obtain the simulated effect images for each stage in one go. Alternatively, the original part image and the effect description text for the first stage can be input into the second major model first to generate the simulated effect image for the first stage; then, the simulated effect image for the first stage can be used as the new original image and the effect description text for the second stage can be input into the second major model to generate the simulated effect image for the second stage; and so on, until the simulated effect images for each stage are obtained.

[0102] In the embodiments of this disclosure, by adding the effect description subtext of each of the multiple stages to the prompt template, since the preset prompt template provides a clear and structured operation instruction framework for the second major model, it can effectively transform the abstract text description into the specific requirements of the image generation task, effectively prevent confusion or information loss of effect descriptions at different stages, and also ensure the standardization and consistency of instruction format through the template, providing clear guidance for the generation process.

[0103] Furthermore, since the instructions in the template explicitly require the model to make sequential and targeted visual modifications to the target parts based on the specific description text of each stage, it not only transforms the abstract text description into a step-by-step visual generation task that the model can accurately execute, but also ensures through the template that the final series of images can follow the stage-by-stage evolution logic derived from professional knowledge reasoning.

[0104] Building upon this foundation, by inputting part information and prompts into the second major model, the part information provides a visual base and style constraints for the generation process, while the prompts provide clear objectives for phased modifications. This allows the second major model to generate a series of simulated images step by step and in a controllable manner based on the real visual features of the original parts and under the precise guidance of the prompts. This ensures that the image at each stage is both a logical evolution of the image at the previous stage and strictly conforms to the expected state defined by the effect description subtext of the current stage, thereby improving the accuracy, credibility, and consistency with the expected effect description of the generated images.

[0105] According to embodiments of this disclosure, image features may further include at least one of the following: object features of the object and environmental features of the captured part image. While extracting the features of the target part itself from the part image, object features and environmental features reflected in the part image can also be identified.

[0106] Object characteristics can be individual attributes related to the object itself that may affect the appearance of the target area or the effectiveness of the product. For example, object characteristics can include statistical characteristics such as age and gender, or biological characteristics such as skin color and basic skin texture. Environmental characteristics can be the physical environmental conditions in which the image of the area was taken. For example, environmental characteristics can include lighting characteristics such as the type of light source, light intensity, direction and uniformity, or background characteristics such as the simplicity or complexity of the background and its color.

[0107] When generating simulated effect images, in addition to using the original part images and the effect description texts for each stage, object features and environmental features can also be used as conditional inputs to the second large model to obtain simulated effect images for each stage.

[0108] For example, object features and environmental features can be encoded into additional text descriptions, concatenated into the original prompts, and then input into the second main model. Alternatively, object features and environmental features can be encoded into independent feature vectors, concatenated with or fused with the encoded text prompt vectors through cross-attention, and then input into the second main model. Another alternative is to first generate an initial effect image based on the original part image and the effect description sub-texts for each stage, and then perform post-processing adjustments on this initial effect image based on the object features and environmental features; these are not limited here.

[0109] In the embodiments of this disclosure, since the image features include at least one of the object features of the object and the environmental features of the image of the shooting location, a deep visual context related to the individual user and the shooting scene can be captured for the subsequent image generation process. By inputting both object features and environmental features into the second model, the second model not only focuses on the pathological state of the scar, but also understands and preserves the user's personalized appearance base and the visual atmosphere of the original photo. That is, when the second model makes visual modifications to the original target area according to the phased prompts, it can be constrained by both object features and environmental features.

[0110] Specifically, object features ensure that the color, texture, and other characteristics of the skin area surrounding the target area are consistent with the user's real skin, avoiding the generation of skin that does not match the user's skin tone, thus guaranteeing a natural integration of the repair effect with the user's own features. Environmental features guide the model to simulate the same or reasonably evolving lighting and shadow effects when generating new images, ensuring that the entire image sequence has consistency and realism in terms of lighting conditions, avoiding the texture-like inconsistency caused by inconsistent lighting. By integrating these features, the generated simulated effect image is ensured to maintain a consistent visual environment tone with the original part image, thereby enhancing the personalized realism and scene consistency of the simulated effect image.

[0111] The following will be based on Figure 4 As an example, the process of generating the expected effect display content for the target part based on the product information and part information of the product will be further explained.

[0112] Figure 4 The illustration shows an example diagram illustrating a process of generating intended effect display content for a target part based on product information and part information of a product, according to an embodiment of the present disclosure.

[0113] like Figure 4 As shown, in embodiment 400 for generating content to display the expected effect, after obtaining the part information 401 of the target part and the product information 402 of the product, feature recognition can be performed on the part image 403 in the part information 401 to obtain image features 404.

[0114] After obtaining image feature 404, image feature 404, product information 402, and part information 401 can be input into the first large model M1 to obtain effect description text 405. Effect description text 405 may include effect description sub-texts for each of multiple stages.

[0115] Based on this, the effect description subtexts for each of the multiple stages can be added to the prompt template 406 to obtain prompt information 407. The part information 401 and prompt information 407 are input into the second large model M2 to obtain the simulation effect images 408 for each stage.

[0116] According to embodiments of this disclosure, the anticipated change process includes multiple stages, and the anticipated effect display content includes sub-display content for each of the multiple stages.

[0117] Operation S230 may include the following operations: according to the display strategy, display the sub-display content of multiple stages to the target object through the interactive interface, wherein the display strategy defines the presentation method of the multiple sub-display content.

[0118] A stage is a sub-time period or key state point that constitutes the expected change process. Each stage can represent a specific period in the expected change process. Sub-display content is the display unit corresponding to each stage. For example, sub-display content can include multimedia elements such as images, text, and videos.

[0119] A presentation strategy is a set of rules used to control the organization and arrangement of multiple sub-presentations on the interactive interface. The presentation method, guided by the presentation strategy, is the specific way the sub-presentations are displayed, determining the final form the user sees and experiences. Examples of presentation methods include sequential progressive display, side-by-side static comparison display, vertical timeline expansion display, and draggable timeline video display.

[0120] After achieving the desired presentation effect, the interactive interface can be used to display multiple stages of sub-content to the target audience according to the presentation strategy. For example, if the presentation method is a sequential, progressive display, the interactive interface can first display the first stage's sub-content in full screen, then display the second stage's sub-content after the audience clicks "next," and so on. Alternatively, if the presentation method is a side-by-side static comparison display, the interactive interface can simultaneously display the current state, the first stage, the second stage, and other stages' sub-content side-by-side; this is not limited to this approach.

[0121] In the embodiments of this disclosure, by dividing the continuous and complex expected changes of the target area under the action of the product into multiple stages, the cognitive load on users to understand and evaluate the overall effect is reduced, enabling users to establish expectations step by step and with a focus. Since each stage has corresponding sub-display content, the targeting of the effect demonstration is enhanced. Based on this, by displaying the sub-display content of each stage to the target audience through an interactive interface according to a display strategy, the optimal presentation method can be flexibly selected according to different user scenarios, terminal devices, or marketing objectives, improving the interactivity, adaptability, and user experience of the display.

[0122] According to embodiments of this disclosure, the presentation method can be a phased static information set. A phased static information set can be understood as discretizing the expected change process into multiple independent phases, and treating the relevant information of each phase as structured data. In this case, according to the display strategy, displaying the sub-display content of each phase to the target object through the interactive interface can include the following operations: displaying the sub-display content of each phase in the interactive interface according to the order of the phases.

[0123] The order of each stage can be determined by the sequence of time or the logic of effect evolution. It can also be defined by stage division rules, such as "Stage 1 (0-1 month) > Stage 2 (1-3 months) > Stage 3 (3-6 months)".

[0124] The specific display method can be configured according to actual business needs and is not limited here. For example, for each stage, the sub-display content of each stage can be displayed horizontally in the form of a list or array. Alternatively, a single long image integrating the content of all stages can be generated, and the sub-display content of each stage can be displayed vertically.

[0125] In addition to the methods described above, a multi-page PDF document or slideshow can be generated, with each page including sub-display content for one stage. Alternatively, the information for each stage can be displayed in a collapsible panel format, such as displaying the sub-display content of the first stage by default, and expanding to show the sub-display content of the second stage only after the user clicks to view the second stage.

[0126] In the embodiments of this disclosure, by utilizing a phased static information set presentation method, the complex and continuous expected change process is deconstructed and solidified into a static set composed of multiple phase units arranged in chronological order. This structured presentation method provides users with clear reference nodes, making it easier for users to carefully understand the expected state of each specific period step by step, reducing the cognitive load of users digesting the entire continuous change process at once. Secondly, the phased static information set format endows the displayed content with good reusability and reference value, allowing users to view and compare the graphic and textual information of any specific stage at any time without dynamic playback, thereby enhancing the autonomy and flexibility of information acquisition.

[0127] By displaying the sub-contents of each stage in the interactive interface according to the order of each stage, this orderly and corresponding display method not only clearly reveals the timeline of the change process to the user, but also achieves synchronous explanation and mutual verification of abstract medical descriptions and concrete visual representations by presenting professional text descriptions and intuitive simulation images side by side at each stage node. It can transform complex, future dynamic changes into a static sequence that is easy for users to digest and understand step by step, reducing the information load for users to understand the expected results and enhancing the readability and comparability of the displayed content.

[0128] The following will be in separate Figure 5A and Figure 5B As an example, the process of displaying the expected content to the target object through an interactive interface will be further explained in this disclosure.

[0129] Figure 5A The illustration shows an example diagram of displaying a set of phased static information to a target object through an interactive interface according to an embodiment of the present disclosure.

[0130] like Figure 5A As shown, in Example 500A, which presents a staged static information set, taking a scar as the target area, a scar removal product as the product, and sub-display content including effect description sub-text and simulated effect images as an example, effect description text for the change process can be generated based on product information and area information. This effect description text can include effect description sub-texts for multiple stages. Simulated effect images for each stage are then generated based on the effect description text.

[0131] Based on this, the sub-display content of each stage can be displayed on the interactive interface in the order of each stage. For example, taking stages including 1-30 days, 30-60 days, and 60-90 days as an example, the interactive interface can sequentially display the effect description sub-text "Scar tissue begins to soften, itching is reduced" and the corresponding simulated effect image 501 for 1-30 days, the effect description sub-text "Raised parts gradually flatten, pigmentation begins to fade" and the corresponding simulated effect image 502 for 30-60 days, and the effect description sub-text "Scar appearance further improves, approaching normal skin" and the corresponding simulated effect image 503 for 60-90 days.

[0132] In addition, the interactive interface can provide a "Re-upload Image Evaluation" button. Users can click this button to re-upload the part images and regenerate the effect description sub-text and simulated effect images for each stage, and then display the updated stage static information set through the interactive interface.

[0133] According to embodiments of this disclosure, the presentation method can be a dynamic interactive video. A dynamic interactive video can be a video medium that allows users to actively control the playback process through interactive operations to view the continuous and dynamic changes of the expected effect on the target area. For example, simulated effect images of each stage can be used as keyframes and arranged on a timeline in the order of the stages. Thus, the dynamic interactive video can be a timeline with a draggable slider, where the slider position corresponds to different stages, and the video image transitions smoothly when dragged.

[0134] In this case, displaying the sub-display content of each stage to the target object through the interactive interface can include the following operations: generating dynamic interactive videos according to the order of each stage and the sub-display content of each stage; and displaying the dynamic interactive videos on the interactive interface.

[0135] The specific display method can be configured according to actual business needs and is not limited here. For example, the sub-display content of each stage can be used as keyframes, and intermediate transition frames can be generated using a video editing library or frame interpolation algorithm to obtain dynamic interactive video. Alternatively, the sub-display content of the previous stage can be used as the starting frame and the sub-display content of the next stage can be used as the ending frame. Using an image generation diffusion model, the sub-interactive video from the previous stage to the next stage can be generated by adjusting the time step, and so on, to gradually generate the overall dynamic interactive video.

[0136] After obtaining the dynamic interactive video, it can be displayed on the interactive interface. For example, users can point their device's camera at a target area of ​​their body, and the AR overlay on the screen will play a dynamic simulation animation of the expected effect in real time, or the user can interactively control the playback, thus achieving a dynamic preview that combines virtual and real elements. Alternatively, the dynamic interactive video can provide navigation buttons for quick overview of stages, such as "Stage 1," "Stage 2," etc., below the dynamic interactive video. Clicking the button will directly jump to the dynamic interactive video and play the segments before and after that stage, while highlighting the effect description subtext of that stage.

[0137] In the embodiments of this disclosure, by utilizing the presentation method of dynamic interactive video, discrete expected states at each stage can be integrated into a visually continuous and smoothly evolving dynamic process. It can intuitively show how the target part gradually changes under the action of the product in the form of animation, thereby constructing a smooth, coherent and vivid overall picture of expected changes. This makes up for the shortcomings of static images in terms of transition and continuity between stages, and enhances the naturalness and expressiveness of the effect display.

[0138] By generating dynamic interactive videos according to the order of each stage and based on the effect description subtext and simulated effect images of each stage, discrete stage snapshots are not only synthesized into a visually coherent evolution sequence, making the simulation of the restoration process more delicate and realistic, but also the logical stages based on professional knowledge are seamlessly transformed into a continuous time flow that conforms to the laws of visual cognition. This continuity simulates the real restoration process, ensuring that the content of the dynamic video is fundamentally consistent with professional expectations, and that the visual evolution is smooth and reasonable.

[0139] By displaying dynamic interactive videos on the interactive interface, users are given the autonomy to actively explore the expected change process. This allows users to intuitively feel how the process from the current state to the target effect occurs gradually. Users can also gain a deeper understanding of the specific effects of the product at each point in time according to their own pace and focus. This improves the flexibility of information acquisition, the immersiveness and naturalness of the simulated effect display, and user participation.

[0140] According to embodiments of this disclosure, the sub-display content includes effect description sub-text and simulated effect image. The effect description sub-text describes the expected state of the target area at a given stage, and the simulated effect image is obtained by processing the part image of the target area according to the effect description sub-text. For further explanation of the description sub-text and simulated effect image, please refer to the relevant content above, which will not be repeated here.

[0141] After displaying the dynamic interactive video on the interactive interface, the following operations may also be included: In response to the interactive operation on the dynamic interactive video, display intermediate display content corresponding to the interactive operation on the interactive interface. The intermediate display content includes intermediate descriptive text and intermediate effect images. The interactive operation is an active operation performed by the user on the playback controls of the dynamic interactive video through the front-end interface, with the intention of changing the playback progress or focus of the dynamic interactive video.

[0142] Interactive actions can include dragging or selecting stages on the timeline of a dynamic interactive video. Dragging the timeline involves the user using a mouse or finger to move a slider on the video playback progress bar to any position other than a predefined keyframe. For example, the user might drag the slider from "Month 1" to a point in "Month 1.5". Selecting stages involves the user directly clicking or selecting a label, button, or specific chapter node on the timeline representing a particular stage. For example, the user might click a button labeled "Stage 3" below the timeline.

[0143] When the interactive operation is located at a key time point that is not a preset stage, intermediate descriptive text and intermediate effect images can be generated or obtained to describe the expected state at that intermediate moment. For example, a series of high-density candidate intermediate descriptive texts and candidate intermediate effect images can be pre-generated. During interaction, the slider position can be mapped to the nearest pre-generated intermediate descriptive text and intermediate effect image for display.

[0144] Alternatively, during interaction, an intermediate effect image can be generated in real-time using image deformation algorithms or AI interpolation models based on the relative position of the slider between two keyframes. This intermediate effect image can then be combined with the effect description text corresponding to each of the two keyframes to generate an intermediate description text. This intermediate display content can be used to smoothly showcase changes in dynamic interactive videos. Smoothly showcasing changes means that during user interaction, the transitions between scenes in the dynamic interactive video are visually continuous and without abrupt changes.

[0145] In addition to the above-mentioned interactive operations, gesture interaction can also be supported, such as swiping left and right on the video screen area of ​​the front-end interface to directly control the progress, and double-tapping the screen to bring up a stage selection menu. Furthermore, voice interaction can also be supported, such as users saying "jump to three months" to select a stage, etc., without further limitation.

[0146] In the embodiments of this disclosure, by responding to interactive operations on dynamic interactive videos, intermediate display content corresponding to the interactive operations is displayed on the interactive interface, transforming users from passive video viewers into active process explorers. This not only enables users to obtain customized graphic and textual details at any instant in the dynamic interactive video, breaking the limitation that pre-synthesized videos can only provide fixed content frames, but also achieves real-time synchronization between user focus and information feedback. This allows users to seamlessly and smoothly explore the expected changes at every minute moment from the start to the end, thereby not only realizing the dynamic visualization of the change process, but also enhancing the user's sense of control and immersion over the expected process of the effect, and improving the completeness of the effect display.

[0147] Since the interactive operations include drag-and-drop operations on the timeline or stage selection operations, dragging the timeline allows users to browse continuously and steplessly to simulate quick previews or fine-tuning; while stage selection operations allow users to jump directly to key stage nodes, providing users with two intuitive and efficient ways to freely backtrack, compare, or focus on specific intervals according to their own understanding of the rhythm and focus of attention, thereby optimizing the efficiency and flexibility of information exploration.

[0148] Figure 5B The illustration shows an example diagram of displaying dynamic interactive video to a target object through an interactive interface according to an embodiment of the present disclosure.

[0149] like Figure 5B As shown, in embodiment 500B where the expected effect display content is a dynamic interactive video, taking a scar as the target area, a scar removal product as the product, and sub-display content including effect description sub-text and simulated effect images as an example, effect description text for the change process can be generated based on product information and area information. This effect description text can include effect description sub-texts for multiple stages. Simulated effect images for each stage are generated based on the effect description text.

[0150] Based on this, dynamic interactive videos can be generated according to the order of each stage, using the effect description sub-text and simulated effect images for each stage. For example, taking stages including 1-30 days, 30-60 days, and 60-90 days as an example, a dynamic interactive video 504 can be generated to dynamically display the sub-display content of each stage, and then displayed on the interactive interface.

[0151] In response to an interactive operation on the dynamic interactive video 504, intermediate display content corresponding to the interactive operation can be displayed on the interactive interface. For example, taking the interactive operation as a drag operation on the timeline 505 of the dynamic interactive video, if the user drags the timeline 505 to the 30-day mark, the intermediate descriptive text "The raised parts gradually flatten and the pigmentation begins to fade" and the corresponding intermediate effect image at the 30-day mark can be displayed.

[0152] In addition, the interactive interface can provide a "Re-upload Image Evaluation" button. Users can click this button to re-upload the part images and regenerate the effect description text and simulated effect images for each stage, and then display the updated dynamic interactive video through the interactive interface.

[0153] According to embodiments of this disclosure, the content to be displayed may further include a mapping address. A mapping address is a unique identifier or link pointing to a specific extended content page, which can be used to link to the extended content page corresponding to the product. For example, a mapping address may include at least one of the following: a Uniform Resource Locator (URL), a Uniform Resource Identifier (URI), an in-app deep link, a QR code, etc.

[0154] Extended content pages may include at least one of the following: product details page, user review page, professional content page, service entry page, and product transaction page. The product details page may include the product's complete specifications, price, purchase options, and detailed ingredient information. The user review page may include feedback from other users. The professional content page may include in-depth explanations of medical principles, user tutorial videos, precautions, and links to relevant research literature. The service entry page may include entry points for services such as online consultation appointments, pharmacist consultations, and after-sales service applications.

[0155] In response to a triggered action on a mapped URL, an extended content page corresponding to that URL can be displayed. A triggered action is an interactive behavior performed by the user in response to the visual representation of the mapped URL on the user interface. For example, a triggered action could be clicking the "View More Details" button with a mouse, or scanning a displayed QR code with a mobile phone camera. After the triggered action, the extended content page corresponding to that mapped URL can be loaded and presented.

[0156] In the embodiments of this disclosure, by integrating a mapping address into the expected effect display content and displaying an extended content page in response to a trigger operation, the mapping address establishes a digital link between the highly personalized expected effect display content and product information. That is, while clearly showing users what effects the product may bring, it proactively and non-intrusively provides a direct path on how to further understand or obtain the product. This can effectively stimulate users' willingness to learn more about the details, verify the information, or take follow-up actions, forming a complete service loop from effect perception to commercial conversion, thereby improving the efficiency of user decision-making and effectively promoting commercial conversion based on visual effect display.

[0157] When users develop a desire to learn more based on their approval of the expected results or curiosity, they can directly access the associated extended content page without leaving the current interface or manually searching. This shortens the path from generating interest to obtaining detailed information, reduces the user's decision-making cost and operational threshold, not only improves the continuity and convenience of the user experience, but also effectively captures the immediate attention that users may have after watching the effect demonstration, thereby enhancing the guidance efficiency of the entire shopping guide or consultation service process.

[0158] According to embodiments of this disclosure, the mapping address may include a product transaction address. A product transaction address is a web address or in-application deep link used to guide users through product purchase, order placement, payment, and other transaction processes. For example, a product transaction address may include at least one of the following: an e-commerce platform product details page URL, a one-click add-to-cart API address, a deep link to a payment page, etc.

[0159] In this case, displaying the extended content page corresponding to the mapped address may include the following: displaying the product transaction interface corresponding to the product transaction address. The product transaction interface may include at least one of the following: a product purchase page, a shopping cart page, and an order confirmation and payment page, etc.

[0160] The product purchase page displays price, specifications, and stock, and provides "Buy Now" or "Add to Cart" buttons. The shopping cart page displays a list of selected products, allows users to modify quantities, apply coupons, and leads to checkout. The order confirmation and payment page allows users to fill in shipping information, select a payment method, and complete the payment.

[0161] The display method of the product transaction interface can be configured according to actual business needs and is not limited here. For example, the H5 page corresponding to the product transaction address can be loaded using the WebView component within the App, or the user can be directly navigated to the natively developed target product transaction interface. Alternatively, a browser can be invoked to open the product transaction address in a new tab to display the product interaction interface.

[0162] In addition to the methods mentioned above, after responding to a trigger operation on the mapped address, the extended content page may not be displayed directly. Instead, the voice assistant may be activated to guide the user to confirm product information and complete the order through voice interaction. No restrictions are imposed here.

[0163] In the embodiments of this disclosure, since the mapping address includes the product transaction address, when generating the expected effect display, the interface that most directly serves business conversion can be accurately associated with and embedded. This not only eliminates the information gap and operation steps that users may need to find the correct purchase link between being interested and being able to purchase, but also ensures that the destination of the guidance path is a clear, effective and executable product transaction interface, thereby strengthening the purposefulness and conversion orientation of the entire shopping guide process.

[0164] When users approve of the expected personalized effects, the product transaction address is triggered, directly leading to the product transaction interface. This eliminates the need to switch applications or re-search for products, achieving a closed loop from the visual perception of personalized effects to instant transaction conversion. This reduces the probability of users dropping out due to cumbersome operations after making a decision. It transforms the purchase intention generated by users after watching the effect demonstration into actual purchase behavior with the shortest path and lowest operating cost, shortening the user's decision-making action path and improving the conversion efficiency of marketing guides. In turn, it improves the commercial conversion efficiency and user service satisfaction of the intelligent shopping guide process.

[0165] The following example, using the product transaction address and the corresponding extended content page as the product transaction interface, further illustrates the content interaction process provided in this disclosure.

[0166] Figure 6A The illustration shows an example diagram of a triggering operation process for a product transaction address according to an embodiment of the present disclosure.

[0167] like Figure 6A As shown, in embodiment 600A, where the expected effect of displaying content includes a mapping address and the mapping address is a product transaction address, in addition to displaying a set of phased static information or dynamic interactive videos, the interactive interface can also provide a "product transaction address" button. Users can access the product transaction interface corresponding to the product transaction address by clicking this button.

[0168] Figure 6B The illustration shows an example diagram of a product transaction interface corresponding to a product transaction address, according to an embodiment of the present disclosure.

[0169] like Figure 6BAs shown in embodiment 600B of the product transaction interface, the product transaction interface can display products that the object is interested in during the current content interaction process and the corresponding product information. Each product can have its own selection box 601 for the object to choose whether to purchase the product.

[0170] In addition, the product transaction interface can also display the total amount of all selected products, 602, and provide a "Buy Now" button, which users can click to trigger the purchase of the selected products.

[0171] The above are merely exemplary embodiments, but are not limited thereto. Other health content interaction methods known in the art may also be included, as long as they can improve the clarity and accuracy of the object's understanding of the product's effects.

[0172] Based on the above-described health content interaction method, this invention also provides a health content interaction device. The following will be combined with... Figure 7 The device is described in detail.

[0173] Figure 7 A block diagram of a health content interaction device according to an embodiment of the present disclosure is shown schematically.

[0174] like Figure 7 As shown, the health content interactive device 700 may include an acquisition module 710, a generation module 720, and a display module 730.

[0175] The acquisition module 710 is used to respond to an object's inquiry about the product's effectiveness by acquiring the part information of the target part of the object through the interactive interface.

[0176] The generation module 720 is used to generate expected effect display content for the target part based on the product information and part information of the product. The expected effect display content presents the expected change process of the target part under the action of the product.

[0177] The display module 730 is used to display the expected effect of the content to the target object through an interactive interface.

[0178] According to embodiments of this disclosure, the generation module 720 may include a first generation submodule, a second generation submodule, and a third generation submodule.

[0179] The first generation submodule is used to generate effect description text for the change process based on product information and part information. The effect description text is used to describe the expected state of the target part at each stage of the change process.

[0180] The second generation submodule is used to generate simulated effect images for each stage based on the effect description text.

[0181] The third generation submodule is used to generate the expected effect display content based on the simulation effect images of each stage.

[0182] According to embodiments of this disclosure, the location information includes a location image of the target location; the first generation submodule may include a feature recognition unit and a first input unit.

[0183] The feature recognition unit is used to perform feature recognition on the part image to obtain image features.

[0184] The first input unit is used to input image features, product information, and part information into the first large model to obtain effect description text.

[0185] According to embodiments of this disclosure, the effect description text includes effect description sub-texts for each of multiple stages; the first generation sub-module may further include a matching unit.

[0186] The matching unit is used to match the reference knowledge base according to the target part type and the product composition to obtain the stage division rules. The reference knowledge base stores the expected improvement characteristics of multiple candidate components for multiple candidate parts at each stage. The stage division rules define the number of stages included in the change process and the expected improvement characteristics of each stage.

[0187] According to embodiments of this disclosure, the first input unit may include a first input subunit.

[0188] The first input sub-unit is used to input the stage division rules, image features, product information and part information into the first large model to obtain the effect description sub-text of each stage.

[0189] According to embodiments of this disclosure, the second generation submodule may include an adding unit and a second input unit.

[0190] An add unit is used to add the effect description sub-text of each of the multiple stages to the prompt template to obtain prompt information. The prompt template includes instructions for processing the target area according to the effect description sub-text of each stage.

[0191] The second input unit is used to input part information and prompt information into the second large model to obtain simulation effect images of each stage.

[0192] According to embodiments of this disclosure, the image features further include at least one of the following: object features of the object and environmental features of the image of the captured location; the second input unit may include a second input subunit.

[0193] The second input sub-unit is used to input at least one of the object features and environmental features, part information, and prompt information into the second large model to obtain the simulation effect images of each stage.

[0194] According to embodiments of this disclosure, the expected change process includes multiple stages, and the expected effect display content includes sub-display content for each of the multiple stages; the display module 730 may include a first display sub-module.

[0195] The first display submodule is used to display the sub-display content of each stage to the target object through an interactive interface according to the display strategy. The display strategy defines the presentation method of the multiple sub-display contents.

[0196] According to embodiments of this disclosure, when the presentation method is a phased static information set, the display submodule may include a first display unit.

[0197] The first display unit is used to display the sub-display content of each stage on the interactive interface in the order of each stage.

[0198] According to embodiments of this disclosure, when the presentation mode is dynamic interactive video, the display submodule may include a generation unit and a second display unit.

[0199] The generation unit is used to generate dynamic interactive videos according to the order of each stage and the sub-display content of each stage.

[0200] The second display unit is used to display dynamic interactive videos on the interactive interface.

[0201] According to embodiments of this disclosure, the sub-display content includes effect description sub-text and simulated effect image. The effect description sub-text describes the expected state of the target part at a stage, and the simulated effect image is obtained by processing the part image of the target part according to the effect description sub-text. The display sub-module may also include a third display unit.

[0202] The third display unit is used to respond to interactive operations on the dynamic interactive video and display intermediate display content corresponding to the interactive operation on the interactive interface. The intermediate display content includes intermediate descriptive text and intermediate effect images. The interactive operations include dragging operations or stage selection operations on the timeline of the dynamic interactive video. The intermediate display content is used to smoothly display the change process in the dynamic interactive video.

[0203] According to embodiments of this disclosure, the intended effect display content also includes a mapping address, which is used to link to an extended content page corresponding to the product; the display module 730 may also include a second display sub-module.

[0204] The second display submodule is used to respond to a triggered operation on the mapped address and display the extended content page corresponding to the mapped address.

[0205] According to embodiments of this disclosure, the mapping address includes the product transaction address; the second display submodule may include a fourth display unit.

[0206] The fourth display unit is used to display the product transaction interface corresponding to the product transaction address.

[0207] According to embodiments of this disclosure, the acquisition module 710 may include a dialogue submodule and a dialogue submodule.

[0208] The dialogue submodule is used to respond to effect consultation requests. It uses an agent to conduct multiple rounds of interactive dialogue with the object through an interactive interface to guide the object to input information about the target area.

[0209] The determination submodule is used to determine the location information based on the dialogue information obtained through multiple rounds of interactive dialogue.

[0210] According to embodiments of this disclosure, the target area includes scars, and the product includes articles for repairing scars.

[0211] According to embodiments of this disclosure, the location information includes at least one of the following: formation time and formation cause, and the image features include at least one of the following: region range, color features, and depth features.

[0212] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as a Field-Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-a-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0213] It should be noted that the health content interaction device part in the embodiments of this disclosure corresponds to the health content interaction method part in the embodiments of this disclosure. The description of the health content interaction device part is specifically referred to in the health content interaction method part, and will not be repeated here.

[0214] Figure 8A block diagram of an electronic device suitable for implementing a health content interaction method according to an embodiment of the present disclosure is shown schematically. Figure 8 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0215] like Figure 8 As shown, a computer electronic device 800 according to an embodiment of the present disclosure includes a processor 801, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 802 or a program loaded from a storage portion 809 into a random access memory (RAM) 803. The processor 801 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 801 may also include onboard memory for caching purposes. The processor 801 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0216] RAM 803 stores various programs and data required for the operation of electronic device 800. Processor 801, ROM 802, and RAM 803 are interconnected via bus 804.

[0217] According to embodiments of this disclosure, the electronic device 800 may further include an input / output (I / O) interface 805, which is also connected to a bus 804. The electronic device 800 may also include one or more of the following components connected to the input / output (I / O) interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a LAN card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output (I / O) interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 810 as needed so that computer programs read from it can be installed into the storage section 808 as needed.

[0218] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the health content interaction method according to the embodiments of this disclosure.

[0219] In this disclosure, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0220] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the health content interaction method provided in the embodiments of this disclosure.

[0221] When the computer program is executed by the processor 801, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0222] According to embodiments of this disclosure, program code for executing computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages.

[0223] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. It should also be noted that in some alternative implementations, the functions indicated in the boxes may occur in a different order than those shown in the drawings.

[0224] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. A method for interacting with health-related content, comprising: In response to a user's inquiry about the product's effectiveness, the system obtains the location information of the target part of the user through an interactive interface. Based on the product information and the part information, expected effect display content is generated for the target part, wherein the expected effect display content presents the expected change process of the target part under the action of the product; and The expected effect is displayed to the target object through the interactive interface.

2. The method according to claim 1, wherein, The expected change process includes multiple stages, and the expected effect display content includes sub-display content for each of the multiple stages. The step of displaying the expected effect content to the target object through the interactive interface includes: According to the display strategy, multiple sub-display contents of each stage are displayed to the target object through the interactive interface, wherein the display strategy defines the presentation method of the multiple sub-display contents.

3. The method according to claim 2, wherein, When the presentation method is a phased static information set, the step of displaying the sub-display content of each of the multiple phases to the target object through the interactive interface includes: The sub-display content of each stage is displayed on the interactive interface in the order of the stages described.

4. The method according to claim 2, wherein, When the presentation method is dynamic interactive video, the step of displaying the sub-display content of each of the plurality of stages to the target object through the interactive interface includes: The dynamic interactive video is generated according to the order of each stage and the sub-display content of each stage; and The dynamic interactive video is displayed on the interactive interface.

5. The method according to claim 4, wherein, The sub-display content includes effect description sub-text and simulated effect image. The effect description sub-text is used to describe the expected state of the target part at the stage, and the simulated effect image is obtained by processing the part image of the target part according to the effect description sub-text. The method further includes: In response to an interactive operation on the dynamic interactive video, intermediate display content corresponding to the interactive operation is displayed on the interactive interface. The intermediate display content includes intermediate descriptive text and intermediate effect images. The interactive operations include dragging operations or stage selection operations on the timeline of the dynamic interactive video, and the intermediate display content is used to smoothly display the change process in the dynamic interactive video.

6. The method according to claim 1, wherein, The expected effect display content also includes a mapping address, which is used to link to the extended content page corresponding to the product; The method further includes: In response to a triggered operation for the mapped address, an extended content page corresponding to the mapped address is displayed.

7. The method according to claim 6, wherein, The mapped address includes the product transaction address; The page displaying the extended content corresponding to the mapped address includes: Display the product transaction interface corresponding to the product transaction address.

8. The method according to any one of claims 1 to 7, wherein, The step of responding to an object's inquiry about the product's effectiveness by obtaining the target area information of the object through an interactive interface includes: In response to the effect consultation request, the intelligent agent engages in multiple rounds of interactive dialogue with the object via the interactive interface to guide the object to input information about the target area; and The location information is determined based on the dialogue information obtained through multiple rounds of interactive dialogue.

9. The method according to any one of claims 1 to 7, wherein, The step of generating expected effect display content for the target area based on the product information and the area information includes: Based on the product information and the part information, an effect description text for the change process is generated, wherein the effect description text is used to describe the expected state of the target part at each stage of the change process; Based on the effect description text, generate simulated effect images for each of the aforementioned stages; and Based on the simulated effect images of each stage, the expected effect display content is generated.

10. The method according to claim 9, wherein, The location information includes a location image of the target location; The step of generating effect description text for the change process based on the product information and the part information includes: Feature recognition is performed on the image of the described area to obtain image features; and The image features, product information, and part information are input into the first large model to obtain the effect description text.

11. The method according to claim 10, wherein, The effect description text includes multiple effect description sub-texts for each stage; The method further includes: Based on the target part type and the product composition, a reference knowledge base is matched to obtain a stage division rule. The reference knowledge base stores the expected improvement characteristics of multiple candidate components for multiple candidate parts at each stage. The stage division rule defines the number of stages included in the change process and the expected improvement characteristics of each stage. The step of inputting the image features, product information, and part information into the first large model to obtain the effect description text includes: The stage division rules, image features, product information, and part information are input into the first large model to obtain the effect description sub-texts for each of the stages.

12. The method according to claim 9, wherein, The step of generating simulated effect images for each stage based on the effect description text includes: Adding the effect description subtexts of each of the multiple stages to the prompt template yields prompt information, wherein the prompt template includes instructions for processing the target area according to the effect description subtexts of the stages; and The location information and the prompt information are input into the second large model to obtain the simulation effect images of each stage.

13. The method according to claim 12, wherein, The image features also include at least one of the following: object features of the object and environmental features of the area where the image was taken; The step of inputting the location information and the prompt information into the second large model to obtain the simulation effect images of each stage includes: The object features and at least one of the environmental features, the location information, and the prompt information are input into the second large model to obtain the simulation effect images of each stage.

14. The method according to claim 1, wherein, The target area includes scars, and the product includes items for repairing the scars.

15. The method according to claim 14, wherein, The location information includes at least one of the following: formation time and formation cause, and the image features include at least one of the following: region range, color features, and depth features.

16. A health content interactive device, comprising: The acquisition module is used to respond to an object's inquiry about the product's effectiveness by acquiring the location information of the target part of the object through an interactive interface; The generation module is used to generate expected effect display content for the target part based on the product information and the part information of the product, wherein the expected effect display content presents the expected change process of the target part under the action of the product; as well as The display module is used to display the expected effect content to the target object through the interactive interface.

17. An electronic device comprising: One or more processors; Memory, used to store one or more computer programs. The characteristic feature is that the one or more processors execute the one or more computer programs to implement the steps of the method according to any one of claims 1 to 15.

18. A computer-readable storage medium having a computer program or instructions stored thereon, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 15.

19. A computer program product comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the steps of the method according to any one of claims 1 to 15.

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