Wisdom monitoring system after keloid operation

Abstract

The invention discloses a keloid postoperative intelligent monitoring system, which relates to the technical field of medical monitoring and comprises a database, a patient information input module, an image management module, an operation processing standard making module, a postoperative management evaluation module, a re-diagnosis reminding module and a communication module. The patient information input module is used for inputting patient information and generating a unique patient ID after inputting; the image management module comprises an image acquisition unit, an image processing unit and an image marking unit; the operation processing standard making module is used for generating personalized operation processing standard suggestions for doctors; the postoperative management evaluation module generates a postoperative management report; the re-visit reminding module generates a re-visit plan; the communication module is used for communicating with a patient or a contact person; the technical effects that postoperative management evaluation is carried out no longer depending on subjective judgment of doctors, a unified evaluation standard is formed, and therefore the postoperative management effect and the patient satisfaction degree are improved are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical monitoring, and particularly to a smart monitoring system for patients after keloid surgery. Background Art

[0002] In the current rapid development of medical informatization, postoperative management, as a key link in the patient recovery process, has become increasingly important. Especially in the field of keloid treatment, postoperative management plays a decisive role in the patient's rehabilitation and evaluation of treatment effects. At present, some medical institutions mainly rely on traditional paper medical records for postoperative management of keloids. Doctors manually record the patient's surgical information, including the surgical method, scar location and area, etc. The follow-up appointment is arranged by manually checking the medical records and notifying the patient by phone, lacking an automated reminder system. For the preoperative and postoperative photos of patients, they are usually stored in the hospital imaging system, with weak association with the medical record information, making it inconvenient to view and compare. In the formulation of surgical plans, it mainly relies on the personal experience of doctors, lacking a standardized generation process based on a large amount of data and system algorithms.

[0003] For the evaluation of postoperative management, existing technologies mostly rely on the subjective judgment of doctors, lacking objective quantitative analysis of key indicators such as scar color, flatness and location. This evaluation method has strong subjectivity and is difficult to form a unified standard, thus affecting the effect of postoperative management and patient satisfaction. Therefore, the existing postoperative management technologies for keloids urgently need to be improved to enhance the quality and efficiency of medical services. Summary of the Invention

[0004] By providing a smart monitoring system for patients after keloid surgery, the present application solves the problem that in the prior art, postoperative management evaluation relies on the subjective judgment of doctors, which has strong subjectivity and is difficult to form a unified evaluation standard, thus affecting the effect of postoperative management and patient satisfaction; and achieves the technical effect of no longer relying on the subjective judgment of doctors for postoperative management evaluation, forming a unified evaluation standard, thereby improving the effect of postoperative management and patient satisfaction.

[0005] This application provides a smart monitoring system for keloid after surgery, including a database, a patient information entry module, an image management module, a surgical treatment standard formulation module, a postoperative management evaluation module, a follow-up reminder module, and a communication module; case data and expert experience data are stored in the database; the patient information entry module is used to enter patient information, and the patient information at least includes basic patient information, surgical method, location and area of keloid. After entry, a unique patient ID is generated, and the information is stored in the database; the image management module includes an image acquisition unit, an image processing unit, and an image marking unit; among them, the image acquisition unit is used to acquire preoperative and postoperative photos of the patient; the image processing unit is used to process the acquired preoperative and postoperative photos; the image marking unit is used to mark the preoperative and postoperative photos; the image analysis unit is used to compare and analyze the patient's preoperative and postoperative photos; the surgical treatment standard formulation module is used to generate personalized surgical treatment standard suggestions for doctors; the postoperative management evaluation module is used to retrieve the patient's surgical information for quantitative evaluation and generate a postoperative management report; the follow-up reminder module retrieves the patient's basic information, surgical information and postoperative management report, and at the same time the database retrieves and matches reference case data, and generates a follow-up plan according to the reference case data; the communication module is used to communicate with the patient or contact person.

[0006] Further, a data analysis and evaluation system is integrated inside the database.

[0007] Further, the case data at least includes the patient's clinical data and follow-up data.

[0008] Further, the marking information of the preoperative photo at least includes patient ID, shooting time, scar location and area; the marking information of the postoperative photo at least includes patient ID, shooting time, surgery time, surgical method, scar location and area.

[0009] Further, the follow-up plan at least includes follow-up time points, expected examination items, and expected intervention measures.

[0010] Further, when the image analysis unit compares and analyzes the patient's preoperative and postoperative photos, it calls the preoperative and postoperative photos, sorts them according to the time line, analyzes the changes in scar color, area and flatness through the image analysis unit and generates surgical information; the generated surgical information is uploaded to the database; among them, the color difference value between the scar color and the normal skin color is calculated using a color recognition algorithm, and the scar boundary is determined through an edge detection algorithm to calculate the change in scar area.

[0011] Further, the surgical information at least includes the patient's surgical method, surgery time, scar color change and area change.

[0012] Further, after the basic information and preoperative photos of the patient are uploaded to the database, the database retrieves and matches the reference case data, and generates standard surgical treatment suggestions based on the reference case data; among them, the postoperative management evaluation module retrieves at least the scar color difference and area information of the patient after surgery.

[0013] Further, the image acquisition unit acquires the follow-up photos of the patient during the follow-up visit; the image marking unit is used to mark the follow-up photos; the marked follow-up photos are uploaded to the database, and at the same time, the postoperative management evaluation module obtains the information corresponding to the follow-up photos and conducts evaluation and analysis to update the subsequent follow-up plan.

[0014] Further, the marking information of the follow-up photos includes at least the patient ID, follow-up time, surgery time, surgery method, scar location and area, and number of follow-up visits.

[0015] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0016] By integrating expert experience and case data in the database, the standardized input and storage of patient information are realized, and the preoperative and postoperative photos are acquired and processed through the image management module, and the image analysis technology is used to quantify the scar changes; the postoperative management evaluation module automatically generates personalized standard surgical treatment suggestions and formulates the follow-up plan based on data analysis; the communication module is responsible for communicating with the patient; it solves the problem that in the prior art, the postoperative management evaluation depends on the subjective judgment of doctors, and this evaluation method has strong subjectivity and is difficult to form a unified evaluation standard, thus affecting the effect of postoperative management and the satisfaction of patients; it realizes that the postoperative management evaluation no longer depends on the subjective judgment of doctors, forms a unified evaluation standard, and thus improves the technical effects of postoperative management and patient satisfaction. Brief Description of the Drawings

[0017] Figure 1 It is a schematic structural diagram of the intelligent postoperative monitoring system for keloid of the present invention;

[0018] Figure 2 It is a schematic diagram of the image management module of the intelligent postoperative monitoring system for keloid of the present invention;

[0019] Figure 3 It is a schematic diagram of the monitoring process of the intelligent postoperative monitoring system for keloid of the present invention;

[0020] Figure 4 It is a schematic diagram of the process of the image acquisition unit of the intelligent postoperative monitoring system for keloid acquiring preoperative photos;

[0021] Figure 5Generate a schematic diagram of the surgical treatment standard recommendation process for the surgical treatment standard formulation module of the keloid postoperative intelligent monitoring system of the present invention;

[0022] Figure 6 Generate a schematic diagram of the postoperative photo acquisition process for the image acquisition unit of the keloid postoperative intelligent monitoring system of the present invention;

[0023] Figure 7 Generate a schematic diagram of the postoperative management report generation process for the postoperative management evaluation module of the keloid postoperative intelligent monitoring system of the present invention;

[0024] Figure 8 Generate a schematic diagram of the follow-up visit plan generation process for the follow-up visit reminder module of the keloid postoperative intelligent monitoring system of the present invention;

[0025] Figure 9 Generate a schematic diagram of the follow-up visit plan update process for the keloid postoperative intelligent monitoring system of the present invention. Detailed implementation manners

[0026] To facilitate the understanding of the present invention, the present application will be described more comprehensively with reference to the relevant attached drawings; the preferred embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0027] It should be noted that the terms "vertical", "horizontal", "upper", "lower", "left", "right" and similar expressions used herein are only for the purpose of illustration and do not represent the only implementation manner.

[0028] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs; the terms used in the description of the present invention in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0029] Example: As Figures 1 to 9 shown, the keloid postoperative intelligent monitoring system of the present application includes a database, a patient information entry module, an image management module, a surgical treatment standard formulation module, a postoperative management evaluation module, a follow-up visit reminder module and a communication module.

[0030] The patient information entry module is used to enter patient information, and the patient information at least includes patient basic information, surgical method, location and area of the keloid. After entry, a unique patient ID is generated and the information is stored in the database.

[0031] It should be noted that the basic patient information includes at least name, gender, and age information.

[0032] The image management module includes an image acquisition unit, an image processing unit, and an image marking unit.

[0033] Among them, the image acquisition unit is used to acquire preoperative and postoperative photos of the patient.

[0034] The image processing unit is used to process the acquired preoperative and postoperative photos, such as image format conversion, image denoising, contrast enhancement, etc.

[0035] The image marking unit is used to mark the preoperative and postoperative photos. Among them, the marking information of the preoperative photos includes at least patient ID, shooting time, scar location and area; the marking information of the postoperative photos includes at least patient ID, shooting time, surgery time, surgery method, scar location and area.

[0036] Specifically, during the process of acquiring preoperative photos, the image management module ensures that the patient is in a relaxed state and the keloid area is fully exposed; cleans the keloid area to avoid the influence of oil stains, dirt, etc. on the shooting effect; uses a non-irritating marker to mark around the keloid for easy comparison after surgery; adjusts the camera position and parameters according to the preset shooting standards; conducts multi-angle and multi-site shooting to ensure a comprehensive record of the keloid state; views the shooting images in real time to ensure that the images are clear and unobstructed, and re-shoots if necessary; marks the processed images and stores them in the database.

[0037] During the process of acquiring postoperative photos, the image management module, same as the preoperative process, ensures that the patient's keloid area is exposed and cleaned; compares the preoperative marks to ensure that the shooting parts are the same; operates according to the same shooting standards as before surgery; ensures the consistency of postoperative photos and preoperative photos in terms of angle, light, etc. for easy comparison; marks the processed images and stores them in the database.

[0038] Furthermore, the image management module also includes an image analysis unit.

[0039] The image analysis unit is used to conduct a comparative analysis of the patient's preoperative and postoperative photos.

[0040] Call the preoperative and postoperative photos, sort them according to the time line, analyze the changes in scar color, area, and flatness through the image analysis unit and generate surgical information; upload the generated surgical information to the database.

[0041] Specifically, the color difference value between the scar color and the normal skin color is calculated using a color recognition algorithm, and the scar boundary is determined through an edge detection algorithm to calculate the change in scar area. Meanwhile, the flatness change of the scar can be evaluated using 3D reconstruction technology (if supported).

[0042] Among them, the surgical information includes at least the patient's surgical method, surgical time, scar color change, and area change.

[0043] For example:

[0044] 1. Calculate the color difference value between the scar color and the normal skin color using a color recognition algorithm:

[0045] Color space conversion:

[0046] Convert the image from the RGB color space to the CIELAB color space because the CIELAB color space is closer to the visual perception of the human eye and is suitable for calculating color differences.

[0047] Color normalization:

[0048] Perform color normalization on the normal skin area and the scar area to eliminate the influence of uneven illumination.

[0049] Color difference calculation:

[0050] For each scar pixel, calculate its CIELAB color difference (ΔE) from the normal skin color. The formula is as follows:

[0051]

[0052] Among them, L, a, and b represent the lightness, red-green chromaticity, and yellow-blue chromaticity in the CIELAB color space respectively.

[0053] Statistics and analysis:

[0054] Perform statistical analysis on the color differences of all scar pixels to obtain the average color difference value between the scar color and the normal skin color.

[0055] 2. Determine the scar boundary through an edge detection algorithm and then calculate the area change:

[0056] Image preprocessing:

[0057] Denoise and enhance the image to highlight the scar edge.

[0058] Edge detection:

[0059] Apply the Sobel, Canny or other edge detection algorithms to identify the boundary of the scar.

[0060] Boundary tracking:

[0061] Track the detected edges to form a closed scar boundary.

[0062] Area calculation:

[0063] Calculate the area of the scar by counting the number of pixels within the scar boundary or using a contour analysis algorithm.

[0064] For pre-operative and post-operative photos, calculate the scar area separately and compare the changes between the two.

[0065] 3. Use 3D reconstruction technology to evaluate the change in flatness:

[0066] 3D reconstruction technology:

[0067] If the device supports it, use structured light, laser scanning, or a multi-camera system to collect 3D data of the scar.

[0068] Reconstruct a 3D model of the scar using 3D modeling software.

[0069] Flatness evaluation:

[0070] Analyze the 3D model, calculate the height change on the scar surface, and evaluate its flatness.

[0071] The flatness can be quantified by calculating parameters such as surface roughness and peak-valley height.

[0072] It should be noted that a large amount of case data and expert experience data are stored in the database, and a data analysis and evaluation system can be integrated inside the database; among them, the case data includes at least the clinical data and follow-up data of the patients.

[0073] The surgical treatment standard formulation module is used to generate personalized surgical treatment standard suggestions for doctors.

[0074] Specifically, when the basic information and pre-operative photos of the patient are uploaded to the database, the database retrieves and matches the reference case data, and generates surgical treatment standard suggestions based on the reference case data.

[0075] Among them, the definition of the reference case is usually based on the following key features:

[0076] Location:

[0077] The reference case should have the same keloid location, such as the face, chest, limbs, etc.

[0078] Color difference:

[0079] The color difference (ΔE) should be within a certain range, such as less than 5 unit color differences.

[0080] Area:

[0081] The area difference is less than a certain percentage, for example, an area difference of less than 10%.

[0082] Scar type:

[0083] The types of keloids should be the same, such as all being hypertrophic keloids.

[0084] Basic patient information:

[0085] The basic information of the patient, such as age, gender, skin type, etc., should be the same or similar. For example, the gender and skin type of the patients are the same, and the ages of the patients are similar (it can be defined that the age difference between patients is within a preset value, that is, patients with similar ages).

[0086] For example, extract the characteristics of the patient's basic information, the location, color, area, type, etc. of the keloid from the database; use similarity calculation methods (such as Euclidean distance, cosine similarity, etc.) to compare the characteristics of the current case with those stored in the database; according to the similarity calculation results, screen out the most similar cases. For example, select the case with the smallest color difference, the closest area, and the same location. Analyze the treatment plans and results of the reference cases, and extract effective surgical treatment criteria and postoperative care suggestions. For example, for a keloid located on the face and with a small area, recommend a fine core excision surgical method and provide a link to a document with detailed surgical operation points and postoperative care precautions; for a large-area keloid, suggest a suitable skin grafting surgical plan and the basis for the selection of the donor site.

[0087] It should be noted that in this embodiment, multiple different surgical treatment standard suggestions can be provided according to dimensions such as scar color and area for doctors to choose.

[0088] The postoperative management evaluation module is used to retrieve the patient's surgical information for quantitative evaluation and generate a postoperative management report.

[0089] Among them, the postoperative management evaluation module retrieves information on the color difference, area, and flatness (if any) of the scar after the patient's surgery.

[0090] Specifically, the postoperative management evaluation module sets a color quantization standard. For example, if the color difference exceeds a certain threshold, it indicates that there may be inflammation or pigment abnormality; by comparing the change in the scar area before and after surgery, the surgical effect and scar recovery are evaluated; for flatness, whether further intervention is needed is judged by measuring the height difference data on the scar surface; according to different scar locations, function and aesthetics impact weight coefficients are set, and a postoperative management report is generated after comprehensive evaluation to provide treatment adjustment suggestions for doctors.

[0091] For example, assume that a patient has a keloid on the face. After surgical treatment, we conduct the following evaluation:

[0092] Color quantization:

[0093] The color difference of the preoperative scar is ΔE = 12, and that of the postoperative scar is ΔE = 4. The reduction of the color difference indicates the alleviation of pigmentation and good recovery.

[0094] Flatness measurement:

[0095] The height difference of the preoperative scar surface is 2 mm, and that of the postoperative scar is 0.5 mm. The flatness has been significantly improved.

[0096] Area change:

[0097] The area of the preoperative scar is 10 square millimeters, and that of the postoperative scar is 5 square millimeters. The area has been reduced by half, indicating the effectiveness of the surgery.

[0098] Comprehensive evaluation:

[0099] Facial scars have a greater impact on aesthetics, so the aesthetic weight is higher. According to the above data, the report generated by the postoperative management evaluation module may recommend continuing to maintain the current treatment plan and having regular follow-up reviews.

[0100] The follow-up reminder module retrieves the patient's basic information, surgical information, and postoperative management report. At the same time, it retrieves and matches the reference case data in the database and generates a follow-up plan based on the reference case data.

[0101] It should be noted that the doctor can manually adjust the generated follow-up plan.

[0102] The communication module is used to communicate with the patient or the contact person.

[0103] Among them, at the set reminder time, communication can be carried out by means of text messages, emails, or voice calls.

[0104] According to each time node in the follow-up plan, confirm the follow-up time and the docking person with the patient in advance.

[0105] Among them, it is possible to choose to confirm the next follow-up time with the patient after the current follow-up visit or a certain time in advance (such as one week).

[0106] After receiving the reminder, the patient needs to confirm the receipt of the information and the follow-up time; if the patient needs to adjust the follow-up time, the system will re-arrange the reminder; according to the patient's confirmation or adjustment, update the follow-up plan and store it in the database.

[0107] On the day of the follow-up visit, the system sends a reminder again to ensure that the patient does not miss the follow-up visit.

[0108] The image acquisition unit collects the follow-up photos of the patient during the follow-up visit, and the image processing unit is used to process the collected follow-up photos, such as image format conversion, image denoising, contrast enhancement, etc.

[0109] The image marking unit is used to mark the follow-up visit photos. Among them, the marking information of the follow-up visit photos at least includes the patient ID, the follow-up visit time (shooting time), the operation time, the operation method, the scar location and area, and the number of follow-up visits.

[0110] The marked follow-up visit photos are uploaded to the database. At the same time, the postoperative management evaluation module obtains the information corresponding to the follow-up visit photos and conducts evaluation and analysis, and the follow-up visit reminder module updates the subsequent follow-up visit plan according to the evaluation results.

[0111] Among them, the postoperative management evaluation module can evaluate the follow-up visit photos according to a large number of cases and data inside the database.

[0112] It should be noted that the follow-up visit plan includes follow-up visit time points, expected examination items, expected intervention measures, etc.

[0113] It should be noted that after the patient's treatment is completed, the corresponding clinical data and follow-up visit data are integrated, statistically stored in the database, and analyzed and fed back to enrich the case data in the database.

[0114] Furthermore, as Figure 3 shown, the intelligent postoperative monitoring process corresponding to this embodiment for keloid includes:

[0115] S1: Patient information collection and surgical registration;

[0116] S2: Surgical execution and information update;

[0117] S3: Formulation of postoperative recovery plan;

[0118] S4: Radiation therapy arrangement (if any);

[0119] S5: Follow-up visit reminder and patient follow-up visit handling

[0120] S6: Postoperative evaluation and plan adjustment;

[0121] S7: Data statistics and analysis feedback.

[0122] It should be noted that if the patient needs to undergo radiation therapy, the radiation therapy item is incorporated into the follow-up visit operation for follow-up visit reminder and subsequent follow-up visit plan arrangement.

[0123] The technical solutions in the above embodiments of the present application at least have the following technical effects or advantages:

[0124] 1. Improve management efficiency: Through centralized information management and automated follow-up visit reminders, the manual operation time of doctors is reduced, and the work efficiency of postoperative management is improved; it is expected that the time for doctors to handle the postoperative management affairs of each patient can be shortened by 30%-50%;

[0125] 2. Reduce the recurrence rate: Timely and accurate follow-up arrangements and postoperative evaluations based on objective indicators can promptly detect recurrence signs and adjust treatment, reducing the recurrence rate of keloids by 20%-30%. For example, through continuous monitoring of indicators such as color and flatness by a system, abnormal hyperplasia of scar tissue can be detected at an early stage and intervened in a timely manner;

[0126] 3. Optimize the surgical plan: Formulating surgical treatment standards based on data and algorithms improves the scientificity and consistency of the surgical plan, helping to enhance the surgical effect and patient satisfaction. According to simulation analysis, after adopting the recommended standardized surgical plan, the surgical success rate can be increased by 15%-20%;

[0127] 4. Facilitate clinical research: A large amount of systematically accumulated patient data and quantitative evaluation results provide rich materials for clinical research on the postoperative management of keloids, which is conducive to in-depth research on the pathogenesis of keloids and influencing factors of treatment effects, and promotes the development of medicine in this field;

[0128] 5. Improve the efficiency of patient information collection and management and reduce human errors;

[0129] 6. Through the image management module, the treatment effect of keloids can be visually monitored, providing decision-making support for doctors;

[0130] 7. The generation of postoperative management reports helps doctors promptly adjust the treatment plan and promote patient recovery;

[0131] 8. The follow-up reminder system improves the follow-up rate of patients, helps to track the recovery of patients, and intervenes in a timely manner.

[0132] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A smart monitoring system for keloid after surgery, characterized in that, It includes a database, a patient information entry module, an image management module, a surgical treatment standard formulation module, a postoperative management evaluation module, a follow-up reminder module, and a communication module; The database stores case data and expert experience data; The patient information entry module is used to enter patient information, which at least includes patient basic information, surgical method, keloid location and area. After entry, a unique patient ID is generated, and the information is stored in the database; The image management module includes an image acquisition unit, an image processing unit, and an image marking unit; Among them, the image acquisition unit is used to acquire preoperative and postoperative photos of the patient; The image processing unit is used to process the acquired preoperative and postoperative photos; The image marking unit is used to mark the preoperative and postoperative photos; The image analysis unit is used to compare and analyze the patient's preoperative and postoperative photos; The surgical treatment standard formulation module is used to generate personalized surgical treatment standard suggestions for doctors; The postoperative management evaluation module is used to retrieve the patient's surgical information for quantitative evaluation and generate a postoperative management report; The follow-up reminder module retrieves the patient's basic information, surgical information, and postoperative management report. At the same time, the database retrieves and matches reference case data, and generates a follow-up plan based on the reference case data; The communication module is used to communicate with the patient or contacts.

2. The keloid postoperative intelligent monitoring system according to claim 1, wherein The database internally integrates a data analysis and evaluation system.

3. The keloid postoperative intelligent monitoring system according to claim 2, wherein The case data at least includes the patient's clinical data and follow-up data.

4. The keloid postoperative intelligent monitoring system according to claim 1, wherein, The marking information of the preoperative photo at least includes the patient ID, shooting time, scar location, and area; The marking information of the postoperative photo at least includes the patient ID, shooting time, surgery time, surgical method, scar location, and area.

5. The keloid postoperative intelligent monitoring system according to claim 1, characterized in that, The follow-up plan at least includes follow-up time points, expected examination items, and expected intervention measures.

6. The keloid postoperative intelligent monitoring system according to claim 1, characterized in that, When the image analysis unit compares and analyzes the patient's preoperative and postoperative photos, it calls the preoperative and postoperative photos, sorts them according to the time line, analyzes the changes in scar color, area, and flatness through the image analysis unit, and generates surgical information; the generated surgical information is uploaded to the database; Among them, the color difference value between the scar color and the normal skin color is calculated using a color recognition algorithm, and the scar boundary is determined through an edge detection algorithm to calculate the change in scar area.

7. The keloid postoperative intelligent monitoring system according to claim 6, wherein, The surgical information at least includes the patient's surgical method, surgery time, scar color change, and area change.

8. The keloid postoperative intelligent monitoring system according to claim 6, wherein When the patient's basic information and preoperative photo are uploaded to the database, the database retrieves and matches reference case data, and generates surgical treatment standard suggestions based on the reference case data; Among them, the postoperative management evaluation module at least retrieves the scar color difference and area information of the patient after surgery.

9. The keloid postoperative intelligent monitoring system according to claim 8, characterized in that, The image acquisition unit acquires the follow-up photos of the patient during the follow-up visit; The image marking unit is used to mark the follow-up photos; The marked follow-up photos are uploaded to the database. At the same time, the postoperative management evaluation module obtains the information corresponding to the follow-up photos and conducts evaluation and analysis to update the subsequent follow-up plan.

10. The keloid postoperative intelligent monitoring system according to claim 9, characterized in that, The marking information of the follow-up visit photos includes at least patient ID, follow-up visit time, surgery time, surgery method, scar location and area, and number of follow-up visits.

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