260 results about "Specialty" patented technology

The invention relates to the technical field of information security management, and discloses an information security management method and system based on digital medical treatment. The method comprises the following steps: verifying doctor professional qualification, patient authorization range, data sensitivity level and time permission validity in a multi-institution medical data access request, and generating a permission verification result; analyzing ontology semantic attributes and sensitivity characteristics of medical search keywords input by a user, and determining a corresponding hierarchical encryption strategy based on the permission verification result; performing homomorphic encryption transformation on the medical term synonym set according to the hierarchical encryption strategy, and constructing a medical ciphertext database; and receiving a medical query request, executing symptom disease association matching and ciphertext state logical reasoning operation in the medical ciphertext database, and outputting an encrypted state search result. According to the method, the privacy leakage risk caused by search behavior trajectory analysis is effectively prevented, and the security and availability of medical data are improved.

Disclosed is a system and method for standalone automated patient referral management. The system comprises an intake module that accepts and processes referrals from diverse referral communication channels as entry points for patient referrals. A processing module undertakes the analysis of patient information to pinpoint a healthcare provider based on a healthcare need, a preference, and a schedule availability. A scheduling module confirms the appointment, and engages in dynamic three-way communication between the patient, the referring entity, and the healthcare provider. A feedback module dispatches feedback to the referring entity, offering a report on an outcome of the appointment. A natural language processing (NLP) module extracts information from conversational speech. The system utilizes algorithms to match patients with the healthcare providers based on criteria including specialty, availability, and patient preferences. A feedback module communicates with the originating EHR systems and provides updates to maintain continuity of care.

The invention discloses an agent interaction method and system for enhancing specific industry knowledge, and belongs to the technical field of artificial intelligence. According to the method, multi-modal original data of a target industry is collected and preprocessed, dominant entities and relationships are extracted based on an industry ontology to generate a triple, and implicit knowledge is fused to construct an iterative mixed knowledge graph; converting a user query into a vector, retrieving a Top-K candidate knowledge vector, and then performing interpretable scoring in combination with a query vector, a candidate vector and a triple to obtain an enhanced feature; and dynamically determining an expert sub-network set, and fusing reasoning results of the experts to generate a final answer. The system comprises a knowledge graph and a feature enhancement and reasoning module, and dynamic updating and accurate reasoning of knowledge are achieved. According to the method, the industry knowledge coverage degree, the reasoning accuracy and the interpretability are improved, the illusion problem of a large language model is relieved, and the method is suitable for intelligent interaction services in the professional fields of medical treatment, finance and the like.

The invention relates to a recording method and system of an electronic medical record, and aims to comprehensively and systematically collect health information of a patient through diversified input terminals, improve information input efficiency, ensure information integrity and promote team cooperation. The system comprises a medical professional terminal, a patient direct related terminal and other patient related terminals, supports information input in various forms of pictures, characters, videos, audios and the like, and covers various input devices such as portable devices, professional examination instruments and the like. And the information storage module ensures accurate homing of the data and supports cross-mechanism data integration and sharing. The system also has the functions of electronic medical record automatic generation, treatment tracking, symptom and sign extraction, intelligent analysis and early warning and the like, provides efficient and accurate information support for medical services, optimizes medical resource configuration, and enhances medical experience of patients. The method is suitable for modern medical management, and particularly has remarkable advantages in the aspect of improving the intelligence and integration level of an electronic medical record system.

The invention relates to the technical field of auxiliary diagnosis and treatment systems, in particular to an intelligent auxiliary diagnosis and treatment system for doctors. Comprising a system initialization and role service registration module, a user input analysis and intention recognition module, an intelligent routing and professional tool set selection module, an SSE streaming response initialization and workflow starting module, a knowledge graph retrieval and reasoning module, a diagnosis and treatment logic reasoning and scheme generation module and a streaming result output and node state updating module. A dynamic knowledge update triggering and verifying module; according to the invention, on the system integration level, efficient integration of multi-professional medical resources is realized based on role-as-a-service architecture, and complete coverage of multi-professional knowledge modules of internal medicine, surgery, oncology and the like is ensured through a role service registration validity evaluation mechanism.

Novel tools and techniques are provided for implementing intelligent assistance (“IA”) or extended intelligence (“EI”) ecosystem for pulmonary procedures. In various embodiments, a computing system might analyze received one or more first layer input data (i.e., room content-based data) and received one or more second layer input data (i.e., patient and / or tool-based data), and might generate one or more recommendations for guiding a medical professional in guiding a surgical device(s) toward and within a lung of the patient to perform a pulmonary procedure, based at least in part on the analysis, the generated one or more recommendations comprising 3D or 4D mapped guides toward, in, and around the lung of the patient. The computing system might then generate one or more XR images, based at least in part on the generated one or more recommendations, and might present the generated one or more XR images using a UX device.

The invention relates to the technical field of medical decision assistance, and particularly discloses a doctor-patient co-decision multi-issue negotiation method and system and a readable storage medium, and the method comprises the following steps: firstly collecting preference information and behavior characteristics of a doctor and a patient for a plurality of negotiation issues; constructing a fuzzy constraint and satisfaction function based on preference information and behavior characteristics; constructing a proxy behavior model based on the fuzzy constraint and the satisfaction function, and forming a distributed negotiation problem; and dynamically optimizing the negotiation strategy through a value function by adopting an ADP (adaptive dynamic programming) algorithm until the negotiation is consistent to generate a common negotiation result or the negotiation fails and terminates the negotiation, and sending a recommendation scheme to the doctor agent and the patient agent. According to the doctor-patient co-decision multi-issue negotiation method and system and the readable storage medium, the negotiation success rate and efficiency are improved, the medical specialty and patient individuation requirements are balanced, the doctor-patient satisfaction is remarkably improved, and the doctor-patient co-decision multi-issue negotiation method and system are suitable for a multi-issue medical decision scene.

According to the time sequence risk control method and system based on the multi-level mixed experts, heterogeneous data in the medical field is fused and mapped to the unified representation space through multi-modal representation learning, and therefore data information is utilized more comprehensively. The system adopts a multi-level hybrid expert (MoE) architecture, tasks can be accurately routed to a more professional expert group according to patient characteristics through a hierarchical gating network, and the accuracy and resource utilization efficiency of the model are greatly improved. Meanwhile, through bidirectional interpretability and a causal inference mechanism, not only can the reason of a risk prediction result be explained, but also anti-fact analysis and specific intervention measure guidance can be provided, so that the model is converted from a pure prediction tool to an intelligent partner for auxiliary decision making.

The invention discloses a traditional Chinese medicine clinical auxiliary decision making system and method based on a multi-mode large language model. According to the method, through a multi-modal information perception and fusion step, visual feature extraction is carried out on a tongue picture image, and the tongue picture image is fused with clinical text semantics; through a case matching step of retrieval enhancement, similar cases are retrieved from a clinical case knowledge base; a clinical auxiliary evaluation report including syndrome discrimination, diagnosis conclusion, traditional Chinese medicine prescription and reasoning process is generated through a context-aware diagnosis generation step; and the clinical rationality of an output result can be ensured by adopting field customization indexes through specialized evaluation steps. A corresponding system comprises a tongue diagnosis generator, a clinical case knowledge base, a diagnosis generator and other components, and end-to-end clinical decision support is achieved. According to the method, the problems of difficulty in integrating multi-modal information, lack of professional data sets and the like in traditional Chinese medicine diagnosis are effectively solved, and doctors are assisted to improve the accuracy and reliability of diagnosis results.

The invention provides a three-dimensional science popularization animation generation method and system based on an AIGC technology, and relates to the technical field of animation generation. The method comprises the following steps: firstly, fusing structured knowledge such as an anatomy term library, a diagnosis and treatment process guide and a drug specification with electronic medical records and CT / MRI volume data, and generating a split script and a medical term list through a large language model; then reconstructing an organ or focus grid by using a script-image combined driven text-three-dimensional diffusion model, and executing anatomical consistency correction according to the medical knowledge graph; automatically arranging a time axis, a camera track and a skeleton action, and synchronously synthesizing multilingual parastyle subtitles; and finally, frame-level rendering and compression packaging are completed in a real-time rendering engine, and efficient, professional and iterable medical animation generation is realized by means of an expert feedback closed-loop fine tuning model.

The invention discloses a security and robustness automatic testing method for a large language model in the medical field, and the method comprises the steps: constructing a field perception harmful problem generator which can automatically learn and map medical knowledge to potential harmful queries; according to the method and the system, the real security boundary of the large language model in the medical field can be efficiently and systematically evaluated, and particularly, the evaluation depth and the evaluation breadth are provided in complicated situations involving professional knowledge misleading or potential harm. A generator is optimized through a customized weighted composite reward function, so that the model is effectively guided to generate a field perception harmful problem which has high harmfulness, is coherent and smooth and conforms to grammar, and the quality and pertinence of a data set are remarkably improved; according to the framework, the dependence on a large amount of time-consuming manual intervention is fundamentally eliminated by integrating automatic scoring and a multi-index similarity filtering mechanism of a hazard detection model.

The invention provides a medical diagnosis reasoning method and system based on multi-agent coevolution, and the method comprises the steps: driving a large-scale language model to decompose a medical problem through a problem decomposition agent, and determining a to-be-retrieved sub-problem through a self-adaptive retrieval agent, and selecting a proper knowledge base and a proper retrieval algorithm to obtain multi-source retrieval data, and verifying that the intelligent agent performs de-reforming synthesis on the data to obtain an integrated abstract. The expert recruitment agent builds an expert team according to the abstract, the expert agent diagnoses and reasones to build a dynamic reasoning library, the reasoning library is iteratively optimized through judgment, cross reasoning and the auto-reflection physician agent, the dynamic convergence controller monitors the reasoning library, iteration is terminated when conditions are met, and a final diagnosis decision is output. According to the method, information is directionally obtained from a plurality of authoritative and professional medical knowledge bases through problem multi-granularity retrieval and population evolutionary reasoning, and reasoning efficiency can be improved while reasoning correctness is guaranteed.

Systems and methods for providing an intelligent network to onboard patients to specialty medications are described herein. A server system for managing communication is configured to receive from a user at a healthcare practice, an electronic request to obtain a medical prior authorization (medPA) for a specialty drug to administer for a patient of the healthcare practice; select, using a rules service, a communication pathway to submit the medPA to a healthcare payer from a plurality of communication pathways; and initiate a connection with the healthcare payer using the selected communication pathway.

The invention relates to a community household rehabilitation resource matching and scheduling method and device based on multiple agents. The method comprises the following steps: dynamically acquiring rehabilitation service demand data and rehabilitation resource data in a community through a data acquisition and preprocessing agent; evaluating the rehabilitation service demand data and the rehabilitation resource data of the patient through a demand evaluation agent, and generating a rehabilitation demand priority of the patient and a professional field preference list of a rehabilitator; generating a rehabilitation resource portrait of the rehabilitation demand priority and the rehabilitator professional field preference list through a resource portrait agent; and performing reinforcement learning on the rehabilitation resource portrait through a matching scheduling agent, and decomposing a matching problem into two sub-tasks of coarse-grained matching and fine scheduling. According to the invention, a solution with adaptive capability is provided for community household rehabilitation resource matching and scheduling, so that the overall level of community household rehabilitation service is improved.

A computer-implemented method of evaluating a user image of a patient to enable identification of a historical twin of the patient. The method includes organizing a plurality of medical images in an archive and receiving from a medical professional each of: (i) a region of interest; (ii) a textual description; (iii) selections for binary criteria; and (iv) weights of weighable criteria. The method comprises using a natural language search to create a relevant set of medical images and creating an optimal set from the relevant set of medical images by discarding medical images from the relevant set based at least on the selections for binary criteria. The method includes image processing medical images in the optimal set using the weight of the features of the region of interest to create medical image results. The relevant set comprises less than ten percent of the medical images in the archive.

The invention provides a medical form generation method and system and related equipment, and the method comprises the steps: receiving a form creation instruction, and analyzing a medical context in the instruction through natural language processing; screening from the specialized template library based on the medical context to obtain a matched basic template, and generating a field candidate set; screening the field candidate set through a collaborative filtering algorithm in combination with medical business rules to obtain a recommended field list; performing form rendering on the basic template according to the recommended field list, and initiating a query request to a clinical term service when a medical term field is rendered; adopting multi-strategy mapping to bind the medical term fields with standard clinical terms in the clinical term service; front-end immediate verification and back-end deep verification mechanisms are deployed for user input of the base template. According to the medical form generation method, context sensing, dynamic term binding and multi-level verification are fused to cooperatively realize form generation, and the flexibility and safety of form generation are improved.

In some aspects, a triage artificial intelligence receives a portion of a conversation between a doctor and a patient, determines, based on the conversation, one or more symptoms associated with the patient, determines that the conversation includes a set of trigger words associated with a particular symptom of the one or more symptoms, selects based on the set of trigger words associated with the particular symptom, a first artificial intelligence specialist in a first medical specialty from a plurality of artificial intelligence specialists, and provides the first artificial intelligence specialist with access to the conversation between the doctor and the patient. The first artificial intelligence specialist provides one or more decision support insights that are sent to a computing device associated with the doctor.

The invention relates to the technical field of artificial intelligence health consultation, and discloses a remote health consultation method and system based on artificial intelligence. The method comprises the following steps: receiving a health consultation request submitted by a user through terminal equipment, wherein the request comprises basic health information of the user and a specific consultation question; the basic health information is preprocessed to generate a standardized health data record, and the problems that existing health information is not uniform in format and difficult to efficiently analyze are solved; the standardized data are input into the trained health assessment model, and comprehensive and objective analysis of the health condition of the user is completed; retrieving associated medical knowledge nodes from a medical knowledge graph according to a model analysis result, and providing a professional medical basis for a consultation scheme; and in combination with the medical knowledge node and the user consultation question, constructing a personalized health consultation scheme and sending the personalized health consultation scheme to the user terminal equipment. The method can quickly respond to the consultation demand of the user, guarantee the scientificity and pertinence of the consultation scheme, and effectively improve the remote health consultation experience.

The invention discloses a medical aid decision-making method and system, a clinical decision-making support instrument and a storage medium. The method comprises the following steps: acquiring medical problem data; performing retrieval enhancement labeling on the medical problem data to obtain problem knowledge fragments; performing semantic fusion analysis on the medical problem data and the problem knowledge fragments according to a fully trained large language model to obtain auxiliary decision data of the medical problem data; wherein the auxiliary decision-making data comprises medical result data and question knowledge fragments; according to the method, professional knowledge fragments related to medical problems are obtained by retrieving enhanced labels, reliable knowledge support is provided for a large language model, illusion or errors possibly generated due to the fact that the large model only depends on training data of the large model are avoided, and medical result data obtained after semantic fusion analysis better conform to medical professional logic; as the auxiliary decision-making data further comprises question knowledge fragments, the output auxiliary decision-making data is associated with the corresponding professional basis, so that the source of the auxiliary decision-making data can be understood conveniently.

The invention discloses a medical insurance payment-oriented disease type cost benchmark model establishment method and application. The method comprises the steps of collecting medical insurance or hospital historical disease type settlement data; performing standardization processing on historical disease category settlement data, and performing data statistics on charging items according to disease categories; establishing a disease cost benchmark model, and calculating benchmark frequency and benchmark number of the disease by using historical disease settlement data; adjusting the obtained benchmark frequency and benchmark number by using a large language model to obtain recommended benchmark frequency and benchmark number; in combination with diagnosis and treatment specifications of professional clinical personnel and clinical habits of an overall planning area, the recommended benchmark frequency and benchmark number are manually adjusted to obtain disease benchmark values, and the disease benchmark values are added into a disease data set. Through the constructed case cost benchmark model, disease cost standardization management is promoted through benchmark management, diagnosis and treatment behavior standardization and medical insurance payment cost management and control are achieved, and the balance between compliance medical treatment and economical medical treatment is achieved.

An integrated medical platform with system and methods for enhancing medical procedures by rapid-data integration, artificial intelligence (“AI”) analyses with real-time, data-driven insights generated by machine learning models, which are executed in real time and continuously evolving to assist medical professionals in providing favorable outcomes. Other aspects of the integrated medical platform are configured to improve quality of procedures, automate regulatory headaches and streamline clinical coordination to improve outcomes and cost. In some embodiments, a unified tracking system is configured to track TAVR procedures introduces hospitals to an integrated, multimodal AI-enabled platform designed as an all-in-one platform configured to improve planning and care coordination of complex procedures. Smart data collection optimizes billing and streamlines registry data capture. It provides predictive clinical guidance powered by privacy-preserving federated deep learning and generative AI improves patient care.

The invention discloses a rehabilitation assistive device assessment method based on multi-agent and RAG technology. The method comprises the following steps: constructing a multi-agent system which comprises a rehabilitation physician agent, an auxiliary tool engineer agent, a nurse agent and a user interaction agent; building a dynamic knowledge base based on an RAG technology, wherein the dynamic knowledge base comprises an auxiliary tool product database, a rehabilitation medicine knowledge base, a clinical case base and an industrial standard base; interacting with the user, and dynamically adjusting the question mode, the language style and the question sequence according to the user type and the answer content; retrieving in a dynamic knowledge base according to the obtained information, and respectively outputting professional evaluation suggestions; and according to the collaborative decision model, integrating professional evaluation suggestions of the rehabilitation physician intelligent agent, the auxiliary tool engineer intelligent agent and the nursing personnel intelligent agent to generate a multi-dimensional auxiliary tool evaluation report and recommendation scheme. According to the method, the efficiency of the evaluation process of the assistive device is higher, and the evaluation result is more accurate and effective.

According to the multi-source retrieval and agent collaborative decision-making medical question-answering system and method, a three-layer retrieval framework is constructed, a local medical knowledge base vector retriever, a PubMed intelligent retriever and an academic deep crawling device are integrated, dynamic fusion of multi-source heterogeneous medical information is achieved, and the medical question-answering efficiency is improved. Through the synergistic effect of the three, the information coverage range is remarkably expanded, more comprehensive and multi-dimensional evidence support is provided for various medical problems, the retrieval efficiency and accuracy of a professional database are effectively improved, and the use threshold of non-professional users is reduced. Meanwhile, the technical scheme of the invention supports dual-scene task processing, can meet diversified medical information requirements, provides reliable reference for diagnosis and treatment decisions of medical staff, also provides structured and high-quality information support for subject investigation of medical researchers, and powerfully promotes intelligence and precision of medical information processing.

The invention relates to the technical field of medical management, and discloses a medical specialist ability index evaluation method, which is characterized by comprising the following steps: data acquisition: collecting multi-dimensional information; constructing an index system, and establishing a multi-dimensional evaluation system; weight distribution: determining a weight coefficient by adopting a scientific method; and calculating a specialist ability index through comprehensive scoring model calculation. The system is characterized in that data acquisition is completed through a hospital system and a database; the basic capability indexes comprise equipment configuration and the like; clinical ability indexes comprise diagnosis and treatment quantity and the like; the scientific research capability indexes comprise scientific research projects and the like; the service capability indexes comprise patient satisfaction and the like; the specialized ability index has a specific calculation formula. The method has the advantages that comprehensive, scientific and dynamic assessment of the clinical specialized ability of the medical institution is realized through the specialized ability assessment method based on multi-dimensional data acquisition, objective weight distribution and a quantitative scoring model.

The invention discloses a clinical auxiliary judgment method based on large model fine tuning, and the method comprises the following steps: S1, collecting multi-modal clinical data, and carrying out the preprocessing of the multi-modal clinical data; s2, fusing the preprocessed multi-modal data, and constructing a training sample set conforming to an instruction fine tuning format; s3, performing multi-round instruction fine tuning on the LLaMA model, and updating parameters by adopting a hierarchical freezing strategy; s4, executing a clinical task by applying the fine tuning model, generating a diagnosis text, and analyzing and extracting a diagnosis result; s5, comparing the diagnosis result with a standard knowledge base to generate structured diagnosis information; s6, calculating a confidence score and screening credible diagnosis information in combination with historical medical records and similar medical records; and S7, outputting clinical auxiliary judgment results sorted according to confidence. According to the method, efficient fusion and intelligent analysis of multi-modal clinical data can be realized, and professional accuracy and result credibility of a large model in clinical auxiliary judgment are improved.

The invention relates to the technical field of artificial intelligence and medical health, in particular to an intelligent medical auxiliary system based on multi-model driving and multi-knowledge-base collaboration, and the system comprises an input layer which is used for receiving a query request submitted by a user in the forms of texts, voices and images; the data storage layer comprises a structured knowledge base, and the data storage layer is used for storing disease knowledge data; the processing core layer is used for receiving a query request, selecting a processing flow according to the query request, and generating a response text and interaction feedback in combination with the data stored in the data storage layer; and the output layer is used for outputting a query result which comprises a response text, an original text source of a retrieval basis and interactive feedback of a training link. The system has the capability of integrating texts, voices and images, creatively adopts a multi-knowledge-base RAG architecture oriented to special injury treatment and daily diseases, can provide professional medical auxiliary services in an off-network environment, and meets high-safety scene requirements.

1.The name of the design product: treatment hospital transfer respirator. 2.The use of the design product: a medical device for intensive care and patient transfer in professional medical institutions. 3.The design points of the design product: the combination of shape, pattern and color. 4.The picture or photo that best shows the design points: perspective view. 5.The design claimed contains color.

Systems, methods, and computer-readable media for providing a decision support solution to medical professionals to optimize medical care through data monitoring and feedback treatment are provided herein. In another embodiment, a computer-implemented method for modeling patient outcomes resulting from treatment in a specific medical area includes receiving patient-specific data associated with a patient, determining a plurality of possible patient states under which the patient can be categorized, a current patient state under which the patient can be categorized and determining probabilities of the patient transitioning from any of the possible patient states to every other possible patient state.

The embodiment of the invention provides a multi-role adaptive interaction method and system based on a stomatology knowledge base, and the method comprises the steps: recognizing a query role when a query signal is received, and obtaining the query content; calling a preset query engine matched with the query role, accessing a pre-constructed knowledge base according to the currently called query engine and the query content, and obtaining a differential diagnosis set containing a plurality of diseases with a sorting relationship; and performing multi-dimensional differential diagnosis reasoning on the diseases in the differential diagnosis set one by one according to the sorting relationship, correspondingly evaluating the comprehensive confidence coefficient of the reasoning result, and when the comprehensive confidence coefficient is not less than a preset threshold value, taking the corresponding disease as a diagnosis disease, and outputting a query report matched with the query role. According to the invention, doctors can be assisted to make professional clinical decisions, and convenient oral common sense popularization services can be provided for patients.

This application discloses a method and system for intelligent generation and quality control of medical documents, relating to the field of medical information technology. The disclosed method and system for intelligent generation and quality control of medical documents acquires multi-source medical data, constructs a medical semantic graph network, performs clinical logical reasoning, generates and verifies medical documents, and updates them based on feedback. It can automatically construct a patient-specific medical knowledge network, identify deep semantic relationships between clinical entities, generate logically rigorous professional descriptions, and improve the quality of medical documents and medical safety.