31 results about "Patient feedback" patented technology

The invention relates to the technical field of health data processing, in particular to a clinical patient self-health management recommendation method and system. Obtaining multi-dimensional health data of the target patient, including a clinical measurement index set and a self-report symptom set, and performing standardized preprocessing on the multi-dimensional health data to generate standardized health data; constructing a personal health state map based on the standardized health data; performing health risk traceability analysis according to the personal health state map, and identifying a key risk node set and a risk propagation path; generating an initial health management recommendation strategy set in combination with a predefined medical knowledge base and patient personalized constraints; and dynamically optimizing the initial health management recommendation strategy set based on the patient feedback data and the health state change information, and outputting an optimized personalized health management recommendation scheme. According to the invention, personalized, precise and dynamic patient self-health management recommendation in a clinical scene can be realized.

The invention discloses a method for testing and evaluating safety effectiveness of a digital therapy product for mental diseases, which relates to the technical field of mental diseases and comprises the following steps: S1, evaluating objective indexes of the digital therapy product; s2, testing a man-machine interaction feedback mode; s3, mapping measurement of product output content and patient feedback; and S4, performing real-time adjustment and optimization. According to the method for testing and evaluating the safety effectiveness of the mental disease digital therapy product, aiming at the mental disease digital therapy product, a special testing and evaluating system is constructed, objective indexes and output contents of the digital therapy product are tested, and in the interaction process of a patient and the product, the safety effectiveness of the product is tested. By detecting data such as micro-expression, electroencephalogram signals and eye movement signals of a user in real time, feedback of a patient is obtained in real time, corresponding relation analysis is conducted on the feedback and output content of a digital therapy product, therefore, the treatment effect of the product can be accurately evaluated, and the accuracy of mental disease diagnosis and treatment is improved.

The invention relates to a respiration guiding system for image examination, which is applied to the technical field of image examination and comprises a respiration monitoring module, a patient feedback module, a control processing module and a physician interaction terminal, a plurality of different target breathing waveforms are pre-stored in the doctor interaction terminal, the control processing module generates real-time breathing waveforms based on breathing waveform signals, time synchronization is conducted on the target breathing waveforms and the real-time breathing waveforms, then the patient feedback module and the doctor interaction terminal are controlled to be displayed in a parallel comparison mode, and a patient is guided to adjust breathing. According to the invention, through ''physician-system-patient'' three-element closed-loop interaction, respiratory training and pre-judgment before scanning and continuous guidance and stable maintenance during scanning are realized, so that the success rate of first scanning is improved, the number of times of repeated scanning is reduced, and the radiation dose risk and medical cost of a patient are reduced.

The invention discloses a disease control state evaluation system and method based on psoriasis patient feedback, subjective feelings of patients on disease control can be captured in clinical and non-clinical scenes, and a concept framework is based on literature and doctor-patient feedback. Different from the past psoriasis PROM, the invention provides a method for comprehensively, standardly and quickly collecting'disease control 'information, and the structure content has value for clinical and scientific research. Statistical analysis shows that good clinical benefits can be obtained when the model is applied clinically, and an effective basis for individualized precise treatment is provided for improvement and self-management of psoriasis, especially chronic diseases in China.

This invention provides a basic jaw pad, a dental instrument, and a preparation method. The basic jaw pad includes a first support portion and a second support portion connected to each other. After the basic jaw pad is installed in the through hole of an orthodontic appliance, at least a portion of the first support portion is located within the cavity of the orthodontic appliance for accommodating the dentition. The first support portion mates with the occlusal surface of the dentition on which the orthodontic appliance is worn. At least a portion of the second support portion is located outside the orthodontic appliance and protrudes towards the occlusal surface of the opposing dentition. The basic jaw pad has a preset basic shape, and at least the material of the second support portion of the basic jaw pad is a polished material. This invention improves the versatility of the basic jaw pad, enabling mass production. Furthermore, clinicians can make real-time adjustments and optimizations based on the target positions of the upper and lower jaws in the patient's occlusal state, the specific situation during actual wear, and patient feedback, thereby improving the orthodontic effect.

The invention belongs to the field of auxiliary medical treatment, and provides a personalized electrical stimulation treatment scheme generation system and method, and the method comprises the steps: obtaining a voice signal of a patient, and extracting voice dynamic change information; acquiring neuromyoelectric signals, heart rate signals and motion information of the patient, and extracting physiological change information; performing association modeling on the voice change information and the physiological change information to generate fusion features for representing a multi-part tremor mode of the patient; performing dynamic generation of personalized electrical stimulation parameters based on the fused features; constraining the dynamic change of the current amplitude, the stimulation frequency and the pulse width within an individually set safety threshold range, and performing protective adjustment in combination with real-time feedback of a patient; and the electrical stimulation module is used for implementing electrical stimulation on a target nerve part in the radial nerve, the median nerve or the ulnar nerve according to the parameters issued by the decision module.

This invention provides an intelligent pre-diagnosis medical history collection system for anesthesia clinics, characterized by: a patient terminal, a physician terminal, and a control terminal; the control terminal includes a consultation module and an analysis module; the consultation module stores consultation templates for the patient terminal to access; the analysis module identifies and analyzes patient feedback information and adds intelligent tags to specific information in the patient feedback information; the patient terminal sequentially calls each sub-module, displays relevant content from the consultation template on the front end of the patient's client, and guides the patient to fill in self-reported information; the physician terminal obtains the patient form with added intelligent tags from the control terminal. This system significantly reduces the interview time for information collection, improves the efficiency and accuracy of anesthesia clinic diagnosis and treatment, and reduces the error rate caused by insufficient experience.

The invention belongs to the technical field of big data medical health, and particularly relates to a maternal and fetal congenital anomaly case tracking system based on regional big data, which comprises a data acquisition module, a data transmission and storage module, a big data analysis module, a case tracking and early warning module, a patient feedback and intervention module and a case database and cloud management module. The system can monitor the health conditions of pregnant women and fetuses in real time, generate abnormal early warning in time, effectively reduce the missed diagnosis rate and misdiagnosis rate of maternal and fetal congenital abnormalities, and perform intelligent analysis on large-scale maternal and fetal health data through the big data analysis module to find potential disease risks, thereby providing decision support for doctors, and improving the diagnosis efficiency of the maternal and fetal congenital abnormalities. Meanwhile, the system not only can monitor health data of individuals, but also can realize large-scale maternal and fetal congenital abnormality case tracking, promote reasonable configuration and allocation of regional health resources, improve the working efficiency of doctors, reduce errors of manual diagnosis and ensure early intervention of maternal and fetal health.

The invention discloses an electronic medical record analysis and personalized rehabilitation recommendation method and system based on a large model, and relates to the technical field of medical information processing and artificial intelligence. Comprising the steps of collecting multi-source medical data of a patient from a hospital information system; preprocessing the multi-source medical data; fusing the preprocessed multi-source medical data, and constructing a multi-modal patient portrait; inputting the constructed patient portrait into a pre-trained artificial intelligence analysis model, and performing multi-dimensional analysis to obtain an analysis result; constructing a personalized rehabilitation recommendation engine; based on the analysis result, generating a rehabilitation recommendation scheme through a personalized rehabilitation recommendation engine; in the execution process of the rehabilitation recommendation scheme, continuously collecting feedback data of the patient, and performing incremental learning and retraining on the artificial intelligence analysis model. According to the method, the electronic medical record can be automatically and accurately analyzed, and the personalized rehabilitation recommendation scheme is generated based on the analysis result.

This invention discloses a multimodal health management method and system for TIPS postoperative care, specifically relating to the field of medical and health management technology. It involves constructing a postoperative multimodal follow-up dataset by collecting patient health consultation records, dietary protein intake records, oral medication adherence records, and doctor-patient feedback records. Through consultation topic classification, protein intake deviation identification, medication adherence breakpoint detection, and feedback tendency determination, a set of behavioral events is extracted. Within the same follow-up period, co-occurrence associations of consultation, diet, medication, and feedback events are established to generate a risk trigger chain for hepatic encephalopathy. Based on the risk trigger chain, the intervention type is determined, generating individualized intervention instructions such as dietary guidance, medication reminders, and health consultation responses. These intervention instructions are then pushed to both the patient and healthcare professionals, collecting execution and treatment feedback and writing it back into the dataset to form a closed-loop follow-up update. Finally, the updated data is used to correct the risk trigger chain and automatically generate intervention instructions for the next cycle.

The invention discloses a risk layering and decision-making method based on interaction of a large language model and a risk model, and the method comprises the steps: obtaining and processing multi-modal clinical data of a patient, generating a structured feature matrix, and inputting a risk prediction model to obtain a multi-dimensional risk spectrum; retrieving evidence-based evidence from the medical knowledge base based on the risk probability exceeding the threshold; combining the feature matrix, the risk spectrum and the evidence, and generating an explanatory report through a large language model and cue word engineering; the model weight or retrieval strategy is dynamically adjusted by comparing the consistency of the intervention priority and the risk probability; performing risk layering according to the adjusted risk spectrum and generating personalized intervention suggestions; and continuously optimizing the model according to a medical intervention result and patient feedback data to form closed-loop iterative updating. According to the method, dynamic risk prediction, explanatory report generation and personalized intervention suggestion are realized, and meanwhile, the clinical application value and decision accuracy are improved based on a doctor feedback and patient data closed-loop optimization model.

The invention provides an active medical performance evaluation and payment system based on a DIKWP semantic hierarchical model (data-information-knowledge-intelligence-intention), and solves the problem that the traditional payment mode is difficult to reflect the medical quality. According to the system, medical services are decomposed into DIKWP five-layer semantic units, semantic association between doctor behaviors and patient curative effects is achieved, a semantic performance bill is generated, and payment is based on actual curative effects instead of the number of services. The system comprises a doctor behavior acquisition module, a patient feedback acquisition module, a semantic mapping module, a performance bill generation module and a payment matching module, and can be applied to hospitals, medical insurance and internet hospitals. The system quantifies the contribution of each medical behavior to the health target of the patient, promotes the medical service to change from'quantity-oriented 'to'quality-oriented', improves the medical quality, enhances the participation degree of the patient, realizes refined payment of medical insurance, and provides technical support for'value-type medical treatment '.

The invention relates to a pelvic floor function screening and rehabilitation integrated system, which belongs to the technical field of medical instruments and comprises an integrated probe assembly, a handheld operation controller, a main control processing and display unit and a patient feedback terminal. The integrated probe assembly integrates a high-definition image system, a self-adaptive cleaning mechanism, an intelligent constraint skeleton and a multi-cavity biomechanical training unit, and pelvic floor morphological observation, electromyographic signal detection and three-dimensional vectorization resistance training can be synchronously achieved. The handheld operation controller is provided with multiple sensors and a humanized operation interface, and accurate and stable operation is ensured. The system fuses multi-modal physiological data in real time through the main control unit, generates a personalized rehabilitation scheme, and provides intuitive biological feedback guidance at a patient terminal. According to the device, seamless connection of pelvic floor function evaluation and rehabilitation treatment is achieved, screening accuracy, training pertinence and operation safety are remarkably improved, an integrated solution is provided for postpartum pelvic floor rehabilitation, and the rehabilitation effect and diagnosis and treatment efficiency are effectively improved.

The invention discloses a diagnosis and treatment rule auditing method based on real-time confidence threshold judgment, and the method comprises the steps: obtaining diagnosis and treatment data, and building a game model in which multiple parties participate according to a doctor diagnosis record, patient feedback information and a supervision auditing record in the diagnosis and treatment data; establishing a causal relationship graph model used for representing the causal relationship among the diagnosis confidence coefficient, the misdiagnosis probability and the audit result, and introducing an intervention variable representing intervention on a confidence coefficient threshold value into the causal relationship graph model; based on the estimation of the influence corresponding to the intervention variable, constructing a correction revenue function containing the influence estimation item; and inputting the corrected revenue function into the game model, determining a strategy combination of each participant by adopting equilibrium solution, and determining a Pareto optimal confidence threshold. The confidence coefficient threshold value can be dynamically adjusted according to the change of the real-time diagnosis and treatment data, so that the examination is remarkably improved. The flexibility and the accuracy are considered, and complex and changeable diagnosis and treatment scenes are effectively dealt with.

The application discloses a brain-computer interface interaction system and method for cerebral infarction rehabilitation training, relates to the technical field of electroencephalogram feature processing, and comprises the following steps: feature extraction is performed on electroencephalogram signal data, comprehensive electroencephalogram feature fusion coefficients are obtained through feature weighting fusion calculation based on the electroencephalogram feature data, feedback signal comprehensive calculation is performed based on patient feedback data, comprehensive signal feedback coefficients are obtained, comprehensive rehabilitation evaluation processing is performed according to the comprehensive signal feedback coefficients and the comprehensive electroencephalogram feature fusion coefficients, comprehensive rehabilitation evaluation coefficients are obtained, and the most suitable rehabilitation processing plan for the patient is finally determined based on the comprehensive rehabilitation evaluation coefficients, so that the rehabilitation process is more suitable for the actual situation of the patient itself, and the rehabilitation effect is improved.

With the above in mind, embodiments of the present invention are related to a method including the steps of: providing a graphical user interface to a medical provider, wherein the graphical user interface displays a first dashboard or a second dashboard based on a criteria, wherein the graphical user interface automatically displays the first dashboard having a patient rounding list when a device is located within a hospital geofence and automatically displays the second dashboard having remote monitoring data when the device is located outside the hospital geofence; sending a secure clinical message to the medical provider when a trigger is met; forming a care team by automatically and dynamically selecting a plurality of care team members from a user database based on a location of each user, shift data of each user, and role data of each user; sending a discharge notification to the provider; and remotely monitoring the patient after discharge via at least one remote monitoring device and patient feedback.

The utility model provides a novel brachial artery fixing component which comprises a fixing supporting plate and a fixing belt, the fixing belt is connected with the bottom face of the fixing supporting plate, the fixing plate comprises a middle layer and an outer layer, the outer layer is made of skin-friendly materials, the inner layer comprises a fixing plate body and a reinforcing piece, and the fixing plate body is made of carbon fiber materials. According to the fixing assembly, the fixing plate is made of light materials such as a carbon fiber plate, under the condition that it is guaranteed that the arms of a patient are fixed, more comfortable feedback force is provided for the patient, and acrylic or a steel plate serves as a reinforcing piece to provide more stable supporting; a unique locking structure is convenient for doctors to observe and patients to operate; the arm of a patient can be effectively fixed, stimulation to a puncture point is reduced, and the occurrence risk of complications is reduced; binding and fixing are carried out through the multiple fixing bands, the working efficiency of medical workers can be improved, and doctors can conveniently observe puncture points and find and handle problems in time. The patient experience can be improved, the activity limitation is reduced, and the comfort of the patient is improved.

The invention provides an implantable closed-loop nerve stimulation system and a control method thereof.The implantable closed-loop nerve stimulation system comprises a local real-time control device, a local optimization control device and a cloud server which are connected in sequence, and a patient feedback device connected with the local optimization control device, the local real-time control device is implanted into the brain and is configured to calculate the signal confidence coefficient of the electroencephalogram signal in the first time window to detect an abnormal electroencephalogram signal, and adjust the length of the first time window based on the first instruction; the local optimization control device is an extracranial portable device configured to: process a patient feedback event within a second time window greater than the first time window, determine a first control policy based on at least one of an electrode impedance change rate, a signal confidence, and the patient feedback event; and the cloud server is configured to analyze the first data in a third time window greater than the second time window and generate an alarm message and / or a second control strategy.

This invention discloses a comprehensive hospital follow-up management system and method, belonging to the field of medical information technology. The system addresses the problems of low efficiency, insufficient supervision, and lack of personalization in existing follow-up models by constructing a hierarchical follow-up architecture. The system includes: a task management module, used to automatically generate and intelligently prompt today's follow-up tasks and overdue follow-up tasks according to preset rules; a hierarchical follow-up execution module, supporting primary clinical follow-up, secondary center follow-up, and tertiary leadership spot-check follow-up, and recording follow-up content and audio recordings; a plan management module, generating personalized follow-up plans for patients based on AI algorithms; a multi-channel interaction module, integrating WeChat push notifications, satisfaction survey QR codes, and patient feedback functions to achieve multi-channel interaction between doctors and patients; and a statistical analysis module, used to generate hospital-wide follow-up and satisfaction statistical analysis reports. This invention achieves streamlined, standardized, and intelligent management of follow-up work, significantly improving follow-up efficiency and the quality of medical services.

A system and method for recommending surgical care providers and protocols using artificial intelligence (AI) and machine learning (ML) is disclosed. The system comprises one or more processors coupled to a memory that stores instructions for receiving healthcare data from various sources, preprocessing the data, training an ML model to generate recommendations, and iteratively refining the model based on patient feedback. The system receives data related to surgical procedures, hospitals, doctors, and pre- and post-operative care, preprocesses the data using techniques such as data cleaning, normalization, and encoding, and trains a neural network model to generate recommendations for selecting optimal hospitals, doctors, and care protocols. The generated recommendations are provided to users via an intuitive interface, and patient feedback is used to retrain and optimize the ML model for continuous improvement.

The invention discloses a real-time monitoring method and system for the state of a colorectal tumor patient, and relates to the technical field of colorectal tumor monitoring, and the method comprises the steps: collecting the health original data of the patient, carrying out the preprocessing, and generating a patient health monitoring data set; performing data analysis and risk assessment operation on the patient health monitoring data set to obtain a physiological risk assessment result; according to the personalized intervention measures, through treatment effect monitoring and feedback adjustment operation, an optimized treatment scheme is obtained; and performing treatment effect monitoring and patient feedback analysis operation on the optimized treatment scheme to generate a health report. According to the invention, through accurate data acquisition and preprocessing, deep analysis and generation of personalized intervention measures, the accuracy and personalization of a treatment scheme are effectively improved.

The invention discloses an intelligent follow-up visit plan generation method and system based on a discharge settlement, and the method comprises the following steps: S1, analyzing the discharge settlement through a trained large language model, extracting key information, and carrying out the structured output; s2, matching the output in the step S1 with hospital information, and establishing a corresponding relationship between a doctor and a department; s3, analyzing the follow-up time, connecting with a hospital scheduling system, generating a follow-up plan, and storing the follow-up plan; s4, a timed reminding function is set, and the patient is notified through multiple channels; and S5, collecting patient feedback information, and synchronously updating the patient feedback information to the database. The intelligent follow-up visit system is obviously superior to the prior art in five dimensions of accuracy, timeliness, reach rate, closed-loop management and cost effectiveness, and an intelligent follow-up visit solution which is capable of landing, extensible, compliant and safe is provided for medical institutions.

A medical device system includes a memory; and processing circuitry in communication with the memory. The processing circuitry is configured to receive parametric data for a plurality of parameters of a patient, determine, based on the parametric data, an atrial fibrillation (AF) burden of the patient over a period of time, wherein the AF burden of the patient over the period of time includes a pattern of increased AF burden; output, for display by a user device, a request to identify whether the patient engaged in each patient behavior of a set of patient behaviors during the period of time; and determine, based on receiving a response indicating that the patient engaged in one or more patient behaviors of the set of patient behaviors, a suggestion to change at least a subset of the one or more patient behaviors to attenuate the pattern of increased AF burden.

A patient intention-driven active diagnosis and treatment process generation mechanism is provided, and a diagnosis and treatment scheme is dynamically adjusted based on a health target and intention. The system collects symptoms, medical history and health targets, and generates a preliminary scheme in combination with a medical knowledge base; patient feedback is monitored in real time, effect deviation is analyzed, and dynamic optimization is carried out when a threshold value is exceeded. The method comprises the following steps: analyzing an intention parameter by NLP; establishing branch flow prediction feedback; continuously monitoring, triggering and adjusting; aI optimizes the unexecuted portion. The traditional Chinese medicine concept of preventing diseases is integrated, and preventive intervention is provided. Diagnosis and treatment individuation and flexibility are improved, doctor-patient communication and trust are enhanced, and intelligent medical development is promoted.

The application discloses an intelligent feedback type orthopedic rehabilitation guidance training system and belongs to the technical field of rehabilitation guidance training.The system comprises the following modules: A1, a data acquisition module, which is composed of various high-precision sensors and can comprehensively acquire various physiological and motion data in the rehabilitation training process of patients; A2, a data transmission and processing module, which ensures that the massive rehabilitation data collected can be rapidly, stably and safely transmitted from the patient end to the data processing module through the data transmission module; and A3, a feedback module, which is divided into a patient feedback submodule and a medical staff feedback submodule as two main lines, and the main lines accurately reach the patients and the medical staff.The application comprehensively collects the rehabilitation training data of the patients through various high-precision sensors, including kinematic parameters, pressure distribution, electromyographic signals and the like, analyzes the data by using advanced algorithms and an orthopedic rehabilitation knowledge base, and can provide the patients with accurate and personalized rehabilitation training schemes and real-time guidance, so that the scientificity and effectiveness of the training are ensured and the rehabilitation quality is improved.

The invention discloses a method and a system for intelligently judging alarm data of a magnetic wave knife based on threshold self-adaption, and relates to the technical field of intelligent data judgment. The magnetic wave knife alarm data intelligent discrimination method based on threshold self-adaption comprises the steps that a training instruction is sent out during preoperative pre-collection, and training double-side pressure values of sensors on the two sides of a handheld double-side pressing device are collected in real time; effectively collected training action data are analyzed, and an alarm threshold value of an alarm device is adjusted to adapt to different individual differences; real-time action data are collected in real time during the operation, and the real-time action data comprise two-side pressure values collected through a handheld double-side pressing device, and the two-side pressure values are actually measured double-side pressure values; and performing analysis according to the real-time action data acquired in real time, and outputting early warning information. According to the invention, intelligence and real-time performance of alarm data processing are realized, and the problem that in the prior art, the patient feedback effectiveness is reduced in the treatment process due to too large manual screening workload of medical staff is effectively solved.

The invention discloses a urinary surgery pre-inquiry method and system based on multi-agent cooperation. The system is driven by a node-routing graph, a dialogue state object is adopted to penetrate through the whole interrogation process, and the system runs according to the workflow of dialogue information collection, case characteristic manuscript formation, integrity auditing, patient confirmation and arbitration and first disease course record generation. The dialogue collection agent guides to obtain information such as chief complaint and accompanying symptoms; the expert manuscript forming agent generates and iteratively perfects structured fields such as current medical history, past history, physique and auxiliary examination, and outputs a control instruction for minimizing a question; an integrity auditing agent performs structure and content verification according to the specialized key point list, and loop inquiry is performed when the content is insufficient; an arbitration agent identifies patient feedback and drives a revised closed loop. The system is internally provided with a hybrid retrieval and rearrangement module, BM25 and vector semantic matching are fused, Top-K evidence-based literatures are selected by combining cross encoder scoring and Z-score normalization, an expert diagnosis agent generates a diagnosis basis with reference clues, preliminary diagnosis, differential diagnosis and diagnosis and treatment plans according to the Top-K evidence-based literatures, and a normalized first disease course record is output. According to the scheme, structured collection, automatic manuscript formation and closed-loop auditing of the inquiry information are achieved, traceable evidence-based support and patient participation are considered, the medical record quality and the doctor working efficiency are remarkably improved, and good expandability and clinical application value are achieved.

Techniques to provide haptic feedback to a patient to help the patient align a medical device to a location on their anatomy. In some examples, the patient may align a recharging device to a medical device that is implanted at the location on their anatomy. In some examples, the electrical stimulation can be delivered in such a way that the patient may or may not be able to feel the electrical stimulation, e.g., experience a paresthesia sensation. The system of this disclosure may intentionally adjust the stimulation intensity to provide patient feedback for alignment, such as alignment of the recharging device with the implanted device. Alignment of the recharging device with the implanted device may improve energy transfer, which may, for example, recharge the implanted device more efficiently.

The present application relates to the technical field of health data processing, in particular to a patient self-health management recommendation method and system for clinical use. Multidimensional health data of a target patient is acquired, including a set of clinical measurement indicators and a set of self-reported symptoms, and the multidimensional health data is standardized and preprocessed to generate standardized health data; based on the standardized health data, a personal health status atlas is constructed; health risk tracing analysis is performed according to the personal health status atlas to identify a set of key risk nodes and a risk propagation path; in combination with a predefined medical knowledge base and patient individualized constraints, an initial set of health management recommendation strategies is generated; based on patient feedback data and health status change information, the initial set of health management recommendation strategies is dynamically optimized to output an optimized individualized health management recommendation scheme. The present application can realize individualized, precise and dynamic patient self-health management recommendation in a clinical scenario.