45 results about "Digital medicine" patented technology

The invention relates to the technical field of digital medical treatment and drug evaluation, in particular to an individualized drug curative effect and safety evaluation method and system based on digital twinborn and causal reinforcement learning. Individualized anti-fact prediction is realized through a patient digital twinning model, and potential curative effects and adverse event risks of different medication schemes can be evaluated on a single patient level. Meanwhile, an off-strategy causal reinforcement learning and dual-robust estimation method is adopted, the individualized value of a long-term sequential medication strategy is evaluated from observed real world data, and the preciseness of causal inference is improved; in addition, a curative effect-safety joint value function is constructed, curative effect benefits, safety risks and compliance cost are uniformly incorporated into the same decision framework, and multi-objective joint optimization is achieved; finally, an interpretability analysis report containing key features, value comparison and risk analysis is provided, the understanding and trust of clinicians on recommendation results are enhanced, and application and popularization in clinical practice are facilitated.

The invention relates to the technical field of medical auxiliary diagnosis, and discloses a hypospadias penis curvature measuring method based on physical simulation inversion. The invention aims to solve the technical pain point that the penile erection curvature and the internal fibrosis focus distribution are difficult to quantify noninvasively and accurately before the operation in the existing hypospadias diagnosis and treatment. According to the method, a standard white mold containing fine anatomical partitions is constructed, personalized geometric mapping is realized by using a static look-around image, and constraint physical parameter inversion is performed in combination with a multi-attitude dynamic stress image, so that the digital twin with real biomechanical properties is reconstructed in a virtual environment. According to the method, the erection bending form can be accurately predicted in the non-erection state, the mechanical property abnormal area range is positioned, operation planning is assisted, experience medical treatment is spanned to accurate digital medical treatment, and the wound diagnosis and treatment and operation risks are remarkably reduced.

The application belongs to the field of digital medicine, and particularly relates to a chronic obstructive pulmonary disease (COPD) differential system based on digital lung sound, a construction method and application thereof. The system comprises a data acquisition module, a preprocessing module, a conversion module, a data module, a data processing module, a data enhancement training module, a deep learning module, a differential module, a grading module and a display module. Digital lung sound records of candidates are collected, converted into mel spectrograms, and diagnosed by using a deep neural network. The candidates are COPD patients, healthy people, or people suffering from other lung diseases, and the disease grade of the COPD patients is given by a device carrying the differential system. The examination only needs to collect lung sounds in clinical or other places, reduces radiation damage and possible infection risk in the conventional diagnosis process, and provides a scheme for early diagnosis of COPD, and improves the diagnosis efficiency of the respiratory department, especially the COPD disease.

The application belongs to the field of artificial intelligence and the field of digital medicine, and relates to a cognitive impairment detection device based on artificial intelligence, a computer device and a storage medium.The device obtains original brain electrical signals of a user, pre-processes the original brain electrical signals to obtain a brain electrical signal sequence, adds a classification mark and position coding to the brain electrical signal sequence to obtain a target brain electrical signal sequence, processes the target brain electrical signal sequence based on an anomaly detection layer in an anomaly detection model to obtain target features, performs prediction processing on the target features based on a full connection layer in the anomaly detection model to obtain a prediction result, generates a numerical comparison result of the prediction result and a preset threshold value, and generates a shallow cognitive impairment detection result corresponding to the user based on the numerical comparison result.In addition, the shallow cognitive impairment detection result can be stored in a blockchain.The application adopts a mode of shallow cognitive impairment detection based on an anomaly detection model, and improves the accuracy of shallow cognitive impairment detection.

The application relates to the fields of artificial intelligence and digital medicine, and proposes a deep learning model self-adaptive testing method based on artificial intelligence and related equipment.The method comprises the following steps: obtaining a deep learning model and test data, the deep learning model can obtain feature representation and classification results of any test data; a first data set for storing the feature representation and the classification results is created; real-time test batches are input into the deep learning model to obtain real-time feature representation and real-time classification results of the test data; the first data set is queried based on the real-time feature representation to construct a feature consistency loss; proxy feature representation of each category in the first data set is calculated to construct a feature uniformity loss; the deep learning model and the first data set are updated based on the feature consistency loss and the feature uniformity loss; and the self-adaptive testing of the deep learning model is completed until a preset condition is met. The application can improve the precision of the deep learning model applied to the field of digital medicine on medical test data.

The application relates to the field of artificial intelligence and digital medicine, and proposes an intention recognition model training method and device based on artificial intelligence, an electronic device and a storage medium. The intention recognition model training method based on artificial intelligence comprises the following steps: performing word embedding on a plurality of natural sentences collected in advance to obtain a sentence vector of each natural sentence; identifying an intention vector and a slot vector of the sentence vector by using a preset semantic coding model; labeling the intention vector and the slot vector to construct a training data set; constructing an initial intention recognition model, training the initial intention recognition model by using the training data set, and obtaining an intention recognition model. The method can jointly train the intention recognition model by using the intention vector and the slot vector of the natural sentence, so that the accuracy of the intention recognition model can be improved.

The application relates to the technical field of artificial intelligence and the field of digital medicine, and provides a model allocation method for edge-cloud cooperative reasoning and an edge-cloud cooperative reasoning method. After model allocation is performed on an edge device and a cloud server, an allocation evaluation result corresponding to the edge device is acquired. For the edge device whose allocation evaluation result does not satisfy an allocation end condition, a new target network model is randomly selected from multiple heterogeneous models for the edge device, a new round of model allocation is performed based on the new target network model, the model allocation scheme is continuously optimized, and the overall reasoning effect of edge-cloud cooperative reasoning is improved.

The present application relates to the technical field of digital medicine and drug evaluation, and particularly relates to an individualized drug efficacy and safety evaluation method and system based on digital twinning and causal reinforcement learning. Through a patient digital twinning model, individualized counterfactual prediction is realized, which can evaluate the potential efficacy and adverse event risk of different drug regimens at the individual patient level. Meanwhile, off-policy causal reinforcement learning and double robust estimation methods are used to evaluate the individualized value of long-term sequential drug strategies from observational real-world data, improving the rigor of causal inference. In addition, a combined efficacy-safety value function is constructed, which unifies efficacy benefits, safety risks, and compliance costs into the same decision framework, enabling multi-objective joint optimization. Finally, an interpretable analysis report is provided, including key features, value comparisons, and risk analyses, which enhances clinicians' understanding and trust in the recommended results, facilitating the application in clinical practice.

A method for secure aggregation, by a server, of client-provided inputs includes receiving, from each of a plurality of clients, a respective client input, for which a commitment is published. The commitments were computed using randomness and are aggregated by at least two super-clients and a sum of the aggregated commitments is published by each super-client. A sum of the received client inputs is published such that validity of the sum is checkable, by the clients, by comparing the sum of the received client inputs to a verification algorithm result that uses a sum of additive shares computed by the clients using the randomness, and by verifying that the published sum of the aggregated commitments is the same for each super-client. The method can be applied to use cases, for example, in digital medicine using medical data or smartcity applications to support decision-making.

The embodiment of the invention provides a test case generation method and device, electronic equipment and a storage medium, belongs to the technical field of computers, and is suitable for the field of financial science and technology and the field of digital medical treatment. The method comprises the steps of obtaining object operation behaviors, clustering the object operation behaviors to obtain an operation behavior cluster which is provided with a target cluster center, performing sequence prediction on the target cluster center through a sequence generation model to obtain an operation behavior sequence, screening out target operation from a preset action space according to the operation behavior sequence, and executing the target operation on the operation behavior sequence to obtain the target behavior sequence, and generating the target test case according to the target behavior sequence, so that the software test efficiency can be improved.

The application discloses a medical intention recognition method and device, a storage medium and computer equipment, relates to the technical field of digital medicine, and mainly aims to solve the problems of poor recognition accuracy and effectiveness of the existing medical intention. The method comprises the following steps: obtaining dialogue text to be recognized; performing recognition on the dialogue text based on an intention recognition model that has completed model training, to obtain a first medical intention, wherein the intention recognition model is trained based on a loss function constructed based on a positive sample pair and a negative sample pair, and text training samples; the positive sample pair and the negative sample pair are determined based on opposite statements in the text training samples; determining a second medical intention matched with the first medical intention based on a generated medical knowledge graph, and generating a medical intention recognition result based on the first medical intention and the second medical intention.

The utility model discloses an intelligent digital medicine basket cleaning machine relates to medicine basket cleaning technical field, specifically includes feeding chamber, cleaning and drying chamber and material stacking car, the top of feeding chamber is provided with first medicine basket conveying structure, one end of first medicine basket conveying structure extends to the outside of feeding chamber, the top of another end of first medicine basket conveying structure is provided with the material baffle, the side away from cleaning and drying chamber of material baffle is provided with the material pushing board, the material pushing board is connected with feeding chamber through electric telescopic link no. The second medicine basket conveying structure is arranged in the cleaning and drying chamber. Adopt the mode of spray cleaning, spray flushing, realize the cleaning of medicine basket, compared with the immersion ultrasonic cleaning, can reduce water resource consumption, and can avoid medicine basket to receive secondary pollution in the cleaning process, and in the cleaning and drying process, medicine basket position can change, can realize all -round cleaning and drying, guarantee cleaning effect.

The application relates to the field of intelligent decision-making and the field of digital medicine, and discloses a video retrieval method and device based on multiple modes, electronic equipment and a storage medium, the method comprising the following steps: querying multiple mode attributes of a to-be-retrieved video, selecting a multiple mode network, and extracting multiple mode features in the to-be-retrieved video; extracting a feature sequence, constructing a fixed cluster group of the feature sequence, performing mean pooling on the fixed cluster group to obtain a pooled cluster group, performing fixed-length alignment on the feature sequence according to the pooled cluster group to obtain an aligned sequence; extracting a feature dimension, aligning the dimension length to obtain an aligned dimension, and determining aligned multiple mode features of the multiple mode features according to the aligned sequence and the aligned dimension; performing feature splicing and feature fusion; performing feature vector coding on a retrieval text, calculating a cosine similarity, and determining a video retrieval result of the retrieval text according to the cosine similarity. The application can realize automatic indexing and retrieval of videos and improve the comprehensiveness of the entire video retrieval process.

Embodiments of the present application disclose an image segmentation method, device and equipment and a storage medium, which can be applied to the field of digital medicine. The method comprises: obtaining a target image to be segmented; determining a local image block in the target image and a global image block matching the size of the local image block; inputting the local image block and the global image block into a preset segmentation network model for image segmentation processing, wherein the preset segmentation network model is configured to: perform feature fusion on the input local image block and global image block, and perform segmentation processing based on the fused target feature information; and determining a segmentation result corresponding to the target image according to the output of the preset segmentation network model. The technical solution of the embodiments of the present application can ensure the accuracy of image segmentation.

The application relates to the fields of computer technology and digital medicine, and discloses an intelligent processing method and system of an SQL statement, a computer device and a medium. The method comprises the following steps: when a data operation request for a database is detected, the data operation request is intercepted and analyzed to generate database connection information; when it is determined that a target SQL script is a preset first type SQL, a target execution plan of the target SQL script is determined according to the database connection information, and a to-be-optimized parameter of the target SQL script is determined based on the plan to optimize the target SQL script. Through real-time interception of the data operation request for preset first type SQL judgment, when it is determined that the target SQL script corresponding to the request is the preset first type SQL, a target execution plan at the current time can be created to determine the to-be-optimized parameter for SQL optimization, so that each data request corresponds to the current latest execution plan, accurate reproduction and optimization of the preset first type SQL can be realized, and the stability of the system is improved.

The invention relates to the technical field of crossing of orthodontics and digital medical treatment, and provides an orthodontic target position generation method based on cranio-maxillofacial skeleton harmony, which comprises the following steps: S1, acquiring multi-modal oral data of a patient, performing registration fusion, and constructing a three-dimensional integrated virtual model containing jaw bones and teeth; s2, performing bone form quantitative analysis, and automatically identifying the bone type and main bony limitation characteristics of the patient; s3, on the basis of the skeleton constraint conditions, solving and generating an individualized skeleton coordination correction target position matched with the skeleton form of the patient through a preset coordination degree evaluation function and a multi-objective optimization algorithm; s4, presenting the individualized bone coordination correction target position and an analysis basis through a visual interaction interface; and S5, by taking the confirmed individualized bone coordination correction target position as a reference, finishing tooth movement sequence planning of invisible correction and correction related component design. The defect of excessive or improper compensation caused by neglecting the skeleton basis in the prior art is overcome.

The application provides a data recording method and device, equipment and a computer readable medium, relates to the field of computers and the field of digital medicine, and comprises the following steps: obtaining a first data packet, then performing vector data packet processing on the first data packet to obtain a corresponding data packet vector, and taking the data packet vector as an independent process of a first user mode protocol stack; taking a dynamic library obtained in advance or in real time as a socket interface, and interacting with the data packet vector as the independent process, and transferring a message of a kernel mode protocol stack to the first user mode protocol stack for loading. The application moves the TCP / IP protocol stack originally implemented in the kernel mode to the user mode through the user mode network protocol stack, can not only avoid the context switching overhead of the user mode and the kernel mode, and optimize the performance consumption loss of the traditional kernel mode protocol stack, but also makes it more convenient to debug the program in the user mode. Moreover, with the iteration of the version, the trial and error cost is greatly reduced by trimming and customizing on the basis of the kernel protocol stack.

The invention relates to the technical field of artificial intelligence, the field of digital medical treatment and the field of financial services, in particular to an interaction information generation method and device, equipment and a medium. According to the method, the historical interaction information and the processing behavior data corresponding to the historical interaction information are analyzed, the interaction information preference corresponding to the interaction object is determined, the content combination mode of the to-be-generated interaction information is determined, and the target interaction information is generated. The method can be applied to business scenes of financial services, medical health and the like, the interaction object is firstly determined during triggering generation, historical interaction information and processing behavior data are analyzed to determine interaction information preference and a content combination mode, a target user is matched from a preset database according to user information, and a recommendation scene is obtained as a scene demand; and generating target interaction information in combination with the keyword, the scene demand and the content combination mode, and sending the target interaction information to the interaction object. Therefore, the interaction object is comprehensively analyzed when the generation of the interaction information is triggered so as to accurately generate the interaction information.

The invention relates to a digital medicine dispensing device which comprises a connecting base body, a connecting shell is arranged at the top of the connecting base body, a fixing shell is arranged in the connecting shell, multiple sets of feeding grooves are formed in the top of the connecting shell, multiple sets of guiding grooves are formed in the top of the fixing shell, and multiple sets of connecting frames are arranged on the outer side of the fixing shell. A guide frame is arranged on the outer side of the connecting frame and located on the outer side of the fixing shell, a limiting assembly is arranged at the end, away from the connecting frame, of the guide frame, a guide plate is arranged at the end, close to the limiting assembly, of the interior of the fixing shell, and a guide assembly is arranged at the end, away from the guide plate, of the fixing shell; a discharging hopper is arranged at the bottom of the fixing shell and extends to the outer side of the connecting shell. The medicine dispensing device has the beneficial effects that the quantity of medicine guided out of the guide frame can be controlled, medicine dispensing is carried out according to the dosage of a patient, and the effect of precisely controlling medicine dispensing is achieved.

The application relates to the fields of artificial intelligence and digital medicine, and provides a mechanical arm control method, device, equipment and storage medium. The method detects left and right images, obtains first and second elliptical boundaries, selects first and second clustering ellipses and performs matching, obtains target left and right ellipses, identifies an initial distance between a desktop cup and an electronic device according to a left center point of the target left ellipse and a right center point of the target right ellipse, identifies a cup diameter of the desktop cup according to first and second left long axis vertices of the target left ellipse and first and second right long axis vertices of the target right ellipse, generates a distance relationship between a mechanical arm and the desktop cup based on a positional relationship between the electronic device and the mechanical arm and the initial distance, and controls the mechanical arm to operate, and the application is suitable for a dynamic scene. In addition, the application also relates to a blockchain technology, and the distance relationship and the cup diameter can be stored in the blockchain.

The application relates to the field of digital medicine, in particular to an emotion recognition method and device based on electroencephalogram (EEG) data, an equipment and a medium. The method is based on a source encoder and a classifier trained based on first type EEG data and corresponding emotion classification results, parameters of the source encoder are used to initialize a target encoder to obtain an initial target encoder, the source encoder and the initial target encoder encode the first type EEG data and second type EEG data respectively, a discriminator is used to discriminate the encoder to which the encoding result belongs, parameters of the initial target encoder are optimized according to the discrimination result, until the loss determined by the discrimination result is minimum, the optimized target encoder is used to encode the second type EEG data, the encoding result is input into the classifier, and a classification result is output as an emotion recognition result corresponding to the second type EEG data. Based on EEG data with a known emotion classification result, emotion recognition of another EEG data can be realized without other marking operations, and the recognition efficiency is improved.

The application provides a construction method of a femoral neck fracture personalized bone grafting guide, and belongs to the technical field of digital medicine, and comprises the following steps: 1, three-dimensional reconstruction; 2, virtual reduction; 3, determining a bone grafting point; 4, determining a bone attachment surface; using the uniform offset tool of 3-matic, the extracted bone attachment surface is uniformly offset by 1-2 mm to the outside (namely, in the direction opposite to the relative bone surface), a fitting part is generated; 5, determining a bone grafting path; 6, generating a Kirschner wire sleeve based on the diameter of the Kirschner wire, and further generating a bone grafting guide. The application realizes effective bone support for the femur by attaching the fitting part to the back of the greater trochanter side of the femur of the patient, and generates a Kirschner wire guide sleeve. By using the bone grafting guide, the Kirschner wire can be accurately guided to the bone defect area, namely the bone grafting target area, in the closed reduction surgery of the femoral neck fracture.

The application relates to the fields of computer technology and digital medicine, and discloses a link encryption method, device and equipment and a storage medium, the method comprising the following steps: obtaining a to-be-encrypted link comprising an inner layer link and an outer layer link; reading an inner layer link parameter from the inner layer link and performing encryption processing to obtain an encrypted string; filling the encrypted string to the inner layer link to obtain an encrypted inner layer link; reading an outer layer link parameter from the outer layer link and performing encoding processing on the outer layer link parameter and the encrypted inner layer link according to the same encoding rule to obtain an encoded outer layer parameter and an encoded inner layer link, and filling the encoded outer layer parameter and the encoded inner layer link to the outer layer link to obtain a target encrypted link. The method solves the problem of poor link encryption effect in the prior art, effectively improves the compatibility, complexity and uniqueness of link encryption by combining encryption, encoding and filling, eliminates the decryption risk when the link is intercepted, effectively improves the security of link transmission, and has the characteristics of high security and strong applicability.

The invention belongs to the technical field of artificial intelligence, and relates to a data query method and device, computer equipment and a storage medium, and the method comprises the steps: judging whether a query request sent by a user is received or not; wherein the query request carries query content; if yes, acquiring identity information of the user, and calling a target assistant instance corresponding to the identity information; based on the target assistant instance, retrieving resource data corresponding to the query content from an independent resource pool; searching knowledge data corresponding to the query content from a personal knowledge base; performing comprehensive reasoning processing on the resource data and the knowledge data based on a reasoning strategy to generate a corresponding reasoning result; generating target answer data based on the reasoning result; and returning the target answer data to the user. In addition, the invention also relates to a block chain technology, and the target answer data can be stored in a block chain. The method can be applied to data query scenes in the financial science and technology field and the digital medical field, and the accuracy and personalization of query processing are effectively improved.

The invention belongs to the technical field of data processing, and relates to an interface test method and device, computer equipment and a storage medium, and the method comprises the following steps: obtaining a test file, and obtaining file parameters of the test file; the file parameters are transmitted into an uploading method corresponding to the uploading interface, and file uploading operation is executed on the file parameters through the uploading method; receiving an uploading result which is returned by the uploading method and corresponds to the file parameter; judging whether the uploading result is uploading failure or not; if yes, converting the uploading result based on a conversion rule to obtain target information; determining an expected result corresponding to the test file based on a verification rule obtained from a rule base; and performing assertion judgment processing on the target information and the expected result, and generating a test result corresponding to the uploading interface. In addition, the test result can be stored in the block chain. The method can be applied to test scenes in the financial science and technology field and the digital medical field, and the test efficiency of the file uploading function of the uploading interface is improved.

The application provides an AI-based peripheral pressure stimulation quantification evaluation method and system. It relates to the fields of digital medicine and artificial intelligence technology. The method comprises the following steps: collecting multi-dimensional pressure stimulation data of peripheral pressure stimulation applied by different body parts or different points of the same part of the user in real time, including pressure intensity, stimulation mode, cycle and frequency parameters; obtaining multi-modal physiological feedback data of the skin and superficial tissues under pressure stimulation through a bionic skin sensing module, including stress distribution changes, local blood flow changes and electromyographic signals; performing AI-driven physiological effect prediction based on the multi-dimensional pressure stimulation data and the multi-modal physiological feedback data to obtain a prediction result; dynamically adjusting pressure stimulation parameters through an adaptive optimization module based on the prediction result and individual characteristics; and generating a personalized stimulation scheme, real-time monitoring data and recorded curative effect through an intelligent control interface. The application improves the precision and intelligent level of peripheral pressure stimulation intervention.

The application discloses an enzymatic colorimetric encoding-decoding system and application for multiple biomarker weighted detection, and belongs to the field of biomedical detection. The enzymatic colorimetric encoding-decoding system can realize the mapping relationship between color and multidimensional biomarkers through direct visual interpretation or simple spectrum analysis. The application further provides an enzymatic colorimetric encoding-decoding method for multiple biomarker weighted detection. By integrating enzyme-catalyzed multicolor reaction, nucleic acid-driven signal amplification and optical encoding-decoding mechanism, the multidimensional biomarker information is converted into quantifiable and visually analyzable optical signals, realizing single-tube multidimensional joint detection, high information density output and rapid disease state discrimination. The application has been successfully applied to early screening of pancreatic cancer, and can be extended to dynamic monitoring of multiple markers of other cancers and infectious diseases in the future, providing an efficient and low-cost solution for precision medicine and digital medicine.

The application relates to the technical field of artificial intelligence, and discloses a content management method based on prompt word question and answer interaction, which comprises the following steps: obtaining an input question of an interaction interface, extracting a prompt word of the input question to obtain an input prompt word of the input question; and sequentially performing key word verification, template expectation verification, individualization verification and emotion abnormality judgment on the input prompt word, so that a feedback answer, an expected template, an individualized answer or a question answer of the input prompt word can be selectively generated through the verification. In addition, the application also relates to the blockchain technology, and data lists can be stored in nodes of the blockchain. The application also discloses a content management device, equipment and medium based on prompt word question and answer interaction. The application can be applied to the field of digital medicine, and the content management based on prompt word question and answer interaction can improve the user experience.

The application relates to the technical field of artificial intelligence and the field of digital medicine, and discloses a medical data processing method, device and equipment based on artificial intelligence and a medium, which comprises the following steps: preprocessing collected initial medical data to obtain a medical sample set; training a multi-modal basic model by using the medical sample set based on a self-supervised learning method to obtain an initial medical analysis model; fine-tuning the initial medical analysis model by using a multi-task learning strategy to obtain a first medical analysis model; optimizing the first medical analysis model by using a multi-objective optimization strategy to obtain a second medical analysis model; improving the second medical analysis model by using a feedback learning method to obtain a target medical analysis model; and evaluating target medical data based on the target medical analysis model to obtain a medical evaluation result. The medical analysis model can be stored in a blockchain. The application improves the evaluation efficiency of medical data and ensures the accuracy of the medical evaluation result.

The application belongs to the field of artificial intelligence and the field of digital medicine, and relates to an image detection method based on artificial intelligence, comprising: acquiring a joint image of a target user; calling a preset feature database; performing irrelevant image screening on the joint image based on the feature database to obtain a corresponding target image; performing compliance verification on the target image based on a preset multi-classification model to obtain a verification result corresponding to the target image; if the verification result is a verification pass, detecting the target image based on a preset detection model to generate a target detection result corresponding to the target image. The application also provides an image detection device based on artificial intelligence, a computer device and a storage medium. In addition, the application also relates to blockchain technology, and error positioning information can be stored in a blockchain. The application can be applied to a joint image detection scene in the field of digital medicine, improves the detection efficiency of joint images, and ensures the accuracy of the generated joint image detection result.