53 results about "Disease management" patented technology

A modular disease management system may provide medication management for a patient. The system may include a base configured to at least partially couple to a tissue site of a patient. The system may further include a medication bladder coupled to the base and configured to maintain medication. The system may further include a medication pump coupled to the medication bladder, comprising a conduit and muscle wire-actuated plungers, wherein the medication pump is configured to cause the medication to flow from the medication bladder through the conduit. The system may further include a cannula insertion device coupled to the medication pump via the conduit, wherein the cannula insertion device comprises a cannula, a spring, and a triggering component, wherein the cannula insertion device is configured to insert the cannula into the tissue site of the patient by actuation of the spring released by the triggering component.

The disease management system can determine a measurement of one or more physiological parameters and can determine a disease event based on the one or more measurements. Furthermore, the disease management system can determine a pose of an individual using a pose sensor. Based on an identification of a disease event and a determination that the pose of the individual corresponds to a first pose, the disease management system can cause at least one of an audible, visual, or vibratory alarm. Based on an identification of a disease event and a determination that the pose of the individual does not correspond to the first pose, the disease management system can cause administration of a medication to the individual.

The invention provides a big data resource service-based patient hierarchical intervention method and system, which are applied to the technical field of medical information, and are used for acquiring full-cycle health data of a patient, generating and updating a patient disease course trajectory sequence, analyzing health index change and trend under short, medium and long time scales, and calculating health scores and steady-state coefficients, so as to realize hierarchical intervention of the patient. A layered intervention scheme is generated, detection and personalized intervention of the health state of the patient are achieved, the timeliness and pertinence of medical intervention can be improved, and the disease management effect is optimized.

This invention relates to the field of medical information technology, and in particular to a method and system for generating clinical multi-agent task sequences. The method includes the following steps: acquiring and structuring core clinical objectives, which include patient basic information, clinical indicators, and disease management goals; decomposing the core clinical objectives into several structured sub-objectives with dependencies and execution order based on a clinical pathway template library and a medical knowledge graph; for each structured sub-objective, splitting it into multiple minimum executable clinical sub-tasks according to a clinical sub-task decomposition rule library, and defining the execution subject type, input / output, and dependencies for each clinical sub-task to construct a sub-task-level directed acyclic graph; integrating the sub-task-level directed acyclic graphs, identifying dependencies across structured sub-objectives, generating a global clinical task directed acyclic graph, and performing dependency verification and clinical logic consistency verification.

An apparatus for generating personalized risk assessments for neurodegenerative diseases includes a computing device that receives user data containing genetic and medical information. It processes the data to create genotype identification and gene detection modules, identifying user genotypes and relevant genetic markers. The user's mitochondrial haplogroup is examined to refine the assessment. A risk calculation module employs machine learning to weigh genetic variants against population-based data, calculating a polygenic risk score (PRS). The PRS forms a personalized risk profile, displayed through a visual interface. The disclosed systems offer a comprehensive approach to accurate risk assessment, enabling targeted interventions and informed decision-making in neurodegenerative disease management.

A modular disease management system may provide medication management for a patient. The system may include a base configured to at least partially couple to a tissue site of a patient. The system may further include a medication bladder coupled to the base and configured to maintain medication. The system may further include a medication pump coupled to the medication bladder, comprising a conduit and muscle wire-actuated plungers, wherein the medication pump is configured to cause the medication to flow from the medication bladder through the conduit. The system may further include a cannula insertion device coupled to the medication pump via the conduit, wherein the cannula insertion device comprises a cannula, a spring, and a triggering component, wherein the cannula insertion device is configured to insert the cannula into the tissue site of the patient by actuation of the spring released by the triggering component.

Diabetes management systems may include a glucose monitoring device adapted to transmit glucose data and at least one accessory in communication with the glucose monitoring device and adapted to provide at least one alarm or alert based on the glucose data.

The invention relates to the technical field of medical image analysis, in particular to a chronic obstructive pulmonary disease severity AI grading method based on a CT image, which comprises an image acquisition module, a feature extraction module, a grading evaluation module and an anomaly detection module. A chest image of a patient is obtained through CT scanning, lesion features are extracted through deep learning, a severity index is calculated in combination with a grading standard, and abnormal conditions are detected. According to the method, the lesion feature extraction precision and the diagnosis efficiency are improved, the manual error is reduced, the diagnosis process of the chronic obstructive pulmonary disease is optimized, the comprehensive assessment capability of complex disease conditions is enhanced, and refined support is provided for disease management.

The invention provides an application of an Oncostatin-M concentration level in diagnosis or auxiliary diagnosis of obesity-related chronic kidney diseases. By combining Mendel randomization (MR) analysis with clinical research, single cell sequencing analysis and animal experiments, the concentration of Oncostatin-M in a serum sample is determined, and the Oncostatin-M can be used as a diagnostic marker of obesity-related kidney diseases (CKD) and is used for clinical auxiliary diagnosis and disease management.

The present application relates to the technical field of rheumatism and immunity disease management, and particularly relates to a remote intelligent management method and system for rheumatism and immunity patients. Clinical indexes, environmental monitoring and life behavior data are acquired to construct a multi-element characteristic vector, which is input into a deep learning network to obtain a disease activity prediction result; the prediction result and the characteristic vector are input into a recurrence risk assessment network containing a collaborative constraint layer, and a consistency correction is performed based on a medical prior constraint to obtain a risk assessment result; a counterfactual replacement is performed on the characteristic vector through a causal inference algorithm, the risk assessment network is input to obtain a counterfactual prediction value, a difference value is calculated as a causal contribution degree, risk driving factors are screened, and quantitative intervention suggestions are generated; and operable early warning information is generated based on the driving factors and the intervention suggestions. The present application improves the accuracy of recurrence risk prediction and the pertinence of intervention suggestions.

The present application relates to the technical field of spinal disease management, and specifically discloses a spinal degenerative disease management path method and system based on big data, which comprises the following steps: collecting multi-source heterogeneous data of spinal degenerative disease in different departments and preprocessing, obtaining a standard data set of multi-source heterogeneous data and extracting structural features, generating a standard structural representation of spinal degenerative disease, setting an adaptive screening mechanism, screening and classifying the standard data set of spinal degenerative disease in combination with the standard structural representation to obtain a classified data set, constructing a knowledge graph of spinal degenerative disease, integrating new patient feature data, constructing a time series monitoring network model for reasoning and prediction, obtaining a patient disease progression trend and a potential risk vector, generating a personalized management path based on the disease progression trend and the potential risk vector output by the time series monitoring network model, which is conducive to improving the accuracy of spinal degenerative disease diagnosis and treatment and providing an adaptive disease management path scheme.

The embodiment of the present specification provides an intelligent disease management method, system and storage medium. The intelligent disease management method comprises: in response to detecting that a target patient meets a view display condition, acquiring patient information of the target patient, the patient information comprising a target disease type, a target disease course and examination information; determining a patient view template based on the target disease type and the target disease course; and generating a target patient view of the target patient based on the patient view template and the examination information, and displaying the target patient view via a first terminal.

This invention discloses the application of total flavonoids from sea buckthorn leaves in the preparation of drugs for treating ulcerative colitis, relating to the pharmaceutical field. Animal experiments of this invention have demonstrated that total flavonoids from sea buckthorn leaves can effectively alleviate clinical symptoms and pathological damage of ulcerative colitis; improve intestinal barrier damage in mice with ulcerative colitis; improve the inflammatory response in mice with ulcerative colitis; improve the decreased secretion of short-chain fatty acids in mice with ulcerative colitis; and regulate the abundance and structure of intestinal flora in mice with ulcerative colitis. It shows promise for developing new anti-ulcerative colitis drugs. Therefore, sea buckthorn leaves can be transformed from waste into a valuable resource, providing solid preclinical research evidence for the subsequent development of special medical foods, health products, or functional teas with sea buckthorn leaf flavonoids as the core component, offering daily nutritional support and disease management for patients with ulcerative colitis.

Described herein are methods and compositions for treatment of diabetes and / or obesity. Bitter oligopeptide molecules formulated for enteric delivery modulate signals involving receptors facing the lumen of the gastrointestinal tract, said signaling related hormones such as glucagon-like peptide-1 (GLP-1) and peptide tyrosine-tyrosine (PYY) that involve inhibition of gastric emptying and appetite. As a novel way to treat diabetes with limited adverse effects the described invention uses body's own endocrine system to treat diabetes, which is an advantage over current therapies that may simply provide disease management without cure or require more radical approaches such as surgical intervention.

The present application belongs to the technical field of intelligent disease management, and particularly relates to a psychological support system and a psychological support and medical closed-loop intelligent management system. The present application provides a personalized dynamic psychological support system for disease initial diagnosis patients and their families, which comprises an AI emotional support video module, and combines voice emotional fluctuation rate (V-Vol), visual situation adaptation index (VSAI) and stress sensitivity index (SSI) parameters to realize visual and personalized emotional support. Based on this, the present application further provides a personalized dynamic psychological support and medical closed-loop management system, which is composed of an AI emotional support video module, a product and resource matching recommendation module, a medical intervention and monitoring module and a feedback monitoring and follow-up support module. The system realizes a continuous intervention closed loop with the patient as the center, and has a wide application prospect in the management of the whole disease course of the patient, especially in the emotional and behavioral intervention aspect.

The invention belongs to the field of medicines, and discloses application of macastine B in preparation of anti-inflammatory, repair-promoting and relapse and metastasis-resisting medicines after liver cancer operation. The invention discloses an application of macastine B in preparation of a medicine for recovering a liver cancer patient after partial liver resection. The macaxantin B can promote liver function recovery, reduce the level of inflammatory factors of liver tissues and serum species, and reduce the tumor recurrence rate and the tumor visceral metastasis rate after tumor excision after an orthotopic liver cancer surgical operation, and compared with simultaneous administration of a liver protection drug and an anti-tumor drug, the macaxantin B has the advantages that the liver metabolism burden is reduced, and the curative effect is improved. And a novel drug treatment choice is provided for disease management of a liver cancer patient in a perioperative period. The invention discloses a medicine for promoting postoperative recovery of an orthotopic liver cancer surgical operation. The medicine comprises an effective therapeutic dose of macastine B and pharmaceutically acceptable auxiliary materials.

The invention discloses a human body biochemical index monitoring device based on intercellular fluid, and belongs to the technical field of medical detection equipment. Comprising an outer shell; the microneedle array module is arranged in the outer shell and comprises a liquid collecting chamber, a plurality of microneedles arranged on the front face of the liquid collecting chamber, a pressure sensor and an electric telescopic module; the collecting and processing module comprises a collecting pipe and a buffer solution pipe which are connected with the outer shell, a micropump is arranged at the liquid inlet end of the collecting pipe, and the micropump is connected with the buffer solution pipe and the liquid collecting chamber through liquid conveying pipes; the index detection module is a microchip integrated with one or more sensors; central control; and a power module. The device realizes automatic and painless collection and multi-index rapid detection of intercellular fluid, has the advantages of high precision, small pain and convenience in use, and is suitable for daily health monitoring and disease management.

This invention discloses a dual-model dynamically coupled method and system for green and intelligent poultry farming, belonging to the field of ecological farming technology. The method includes: predicting the change curve of environmental parameters in future periods based on environmental data, and constructing an environmental dynamic compliance model with the objective of minimizing the deviation of the change curve from a preset healthy environment range while simultaneously minimizing the weighted sum of energy consumption of the executing equipment, thereby generating an environmental control command sequence; quantitatively analyzing environmental data, sound data, and video data to calculate a disease risk index and environmental risk factors, and constructing a disease risk prediction model; inputting the disease risk index and environmental risk factors into the environmental dynamic compliance model to obtain an updated environmental control command sequence, and dynamically adjusting the feeding management plan in conjunction with the disease risk index to generate manure scheduling commands. This invention solves the defects of the separation and lagging control between environmental and disease management, achieving the goal of healthy, environmentally friendly, and efficient circular farming.

This invention relates to an AI-based full-lifecycle health intervention method, comprising: constructing a metaverse virtual space for health management; creating and maintaining a dynamic virtual health record for each patient, serving as their digital twin and core data hub; providing rehabilitation activities to patients in the space through virtual avatars configured for users, supporting real-time multi-party interaction, with multi-dimensional health data generated during the process being collected in real time and updated to the record; using a multimodal time-series prediction model to perform real-time analysis and trend prediction of the health data, generating risk prediction information; and triggering and executing personalized health intervention measures based on this information. This invention achieves the integration and continuous management of patients' full-dimensional health data, completing the transformation from a passive response to a proactive early warning disease management model, and providing Alzheimer's patients with an immersive, proactive, and full-cycle comprehensive health management solution by constructing an online and offline linked closed-loop intervention system.

A use of S100A8 / A9 in assessing the severity of infectious diseases, and a use of a biomarker (S100A8 / A9) and / or a substance for detecting the biomarker in the preparation of a product for assessing the severity of infectious diseases. By detecting the level of S100A8 / A9 in serum or plasma, the severity of infectious diseases is rapidly and accurately assessed, thereby simplifying an assessment process and improving accuracy, and the present invention is suitable for various infectious diseases. The biomarker exhibits high sensitivity and good specificity; by assessing the severity of diseases, the present invention provides decision-making support for clinicians, and provides more precise treatment schemes for patients, thereby improving therapeutic efficacy and the quality of life of the patients; and additionally, optimal disease management is achieved, the medical burden on patients' families and society is reduced, and the present invention has favorable and broad clinical application value.

The invention relates generally to medication therapy and more particularly to a system and methods for medication therapy management to support improved adherence and alert clinicians of changes in behavior or symptoms. The system may facilitate interactions between various data sources (e.g., medical health records, genomics databases, and other connected third-party devices) to manage workflow, execute rules, interface with knowledge bases, codify information, schedule events, provide notification, and more. In addition, the system may include a conversational or actionable artificial intelligence persona tailored to each user and configured to, for example, converse, instruct, and / or coach a user according to one or more features of the system. Advantageously, the system may improve adherence and facilitate patient engagement, care transition, and disease management, resulting in, for example, reduced healthcare costs for providers and payers, and enhanced drug use for pharmaceutical manufacturers, pharmacies, and specialty pharmacies.

The embodiment of the invention relates to a skin disease management building system based on multi-modal medical data and a method thereof. The system comprises a data collection module, a data processing module and a federal learning module. The data collection module is used for collecting multi-modal data; the data processing module is used for generating global feature data from the multi-modal data; and the federated learning module is used for performing federated learning by using the global feature data in combination with the central server so as to obtain an auxiliary diagnosis model. According to the technical scheme provided by the embodiment of the invention, through close combination of multi-modal data integration, federal learning, real-time data processing and analysis and cross-mechanism data collaboration, a privacy-protecting, efficient and intelligent skin disease management building system is formed.

The invention provides a turnout static inspection result voice intelligent input method and device, and the method comprises the steps: obtaining turnout static inspection voice information, and converting the turnout static inspection voice information into an original text through a turnout static inspection voice model in combination with a preset prompt word; processing the original text by using a multi-mode character string matching automaton for turnout static inspection to obtain a corrected turnout static inspection text; performing semantic retrieval on the corrected text based on a turnout static inspection knowledge base, and matching out turnout domain knowledge; in combination with the knowledge, supplementing and splitting the corrected turnout static inspection text through a turnout static inspection big language model to obtain turnout static inspection disease information item points; according to the method, through proper noun error correction and turnout field knowledge, the disease information is supplemented and generated, the problem of professional term misjudgment of general voice recognition is avoided, the defects that manual input efficiency is low and data is prone to error are overcome, turnout static inspection diseases can be accurately recognized, and technical support is provided for data statistics and disease management.

The invention relates to the technical field of plant disease treatment, and discloses a disease treatment method, system, equipment and medium for plants in a dry-hot valley, and the method comprises the steps: judging the disease type and severity through image intelligent recognition, and avoiding the prevention and treatment failure and pesticide waste caused by the misjudgment of a traditional empirical method. The pertinence and the success rate of plant disease treatment of the dry-hot valley can be improved; chemical or biological treatment is preferentially adopted for large-scale planting and non-large-scale planting respectively, accurate chemical treatment is conducted in time when the biological treatment is invalid, and the use amount of chemical pesticide is reduced to the maximum extent; agricultural measures such as pruning, sun shading and irrigation are synchronously implemented in combination with pathogenesis analysis to eliminate environmental factors inducing diseases, and the method is suitable for sustainable plant protection requirements under fragile ecology of dry and hot valleys.

A system for generating a sustenance plan for managing genetic disorders is disclosed. The system includes a computing device. The computing device is configured to receive an input which may include genetics test data. The computing device is configured to identify a plurality of biological indices of a disease state as a function of the genetics test data. The plurality of biological indices comprises at least one biological index related to a genetic disease state. The computing device is configured to generate a genetic disorder classifier. The computing device is configured to produce a homeopathic program as a function of the genetic disorder. A method for producing a homeopathic program for managing genetic disorders is disclosed.

This invention relates to the field of medical information technology, specifically disclosing an intelligent follow-up and re-examination reminder system for outpatients throughout their entire treatment cycle. Targeting the management of chronic brain diseases, this invention integrates personalized pharmacokinetic modeling and a cross-validation mechanism of subjective and objective data. By continuously collecting and analyzing patients' micro-movement and vital sign data, combined with an individualized drug concentration theoretical model, it achieves accurate assessment of changes in the patient's condition. Simultaneously, it utilizes subjective and objective cross-validation to ensure data reliability and adopts an event-driven model, transforming traditional periodic follow-up into real-time response management based on key pathological events. The system also features an intelligent re-examination scheduling function, which can automatically adjust the re-examination plan and generate emergency re-examination reminders based on changes in the patient's condition and drug efficacy assessment results, forming a fully automated closed-loop management process. This invention improves the accuracy, timeliness, and patient satisfaction of chronic brain disease management, bringing a new breakthrough to the field of medical information technology.

The invention discloses a gastrointestinal tract disease management system and method based on artificial intelligence, and relates to the technical field of artificial intelligence and gastrointestinal tract disease management, and the system comprises a multi-modal data and knowledge base construction module, an intelligent reasoning and decision generation module and a full-cycle application service module. The multi-modal data and knowledge base construction module obtains gastrointestinal disease data of a target patient and constructs a multi-disciplinary knowledge base. And the intelligent reasoning and decision generation module retrieves related data and knowledge by utilizing a retrieval enhancement generation technology according to a data request containing diagnosis and treatment situation information, and generates illness condition abstract data and index time sequence change data through a large language model after medical text adjustment. And the full-cycle application service module generates health management information according to the data and provides the health management information for a target user. According to the invention, through modular cooperation, multi-source data and knowledge are integrated, accurate illness state analysis and health management information is generated, and the whole-cycle service from hospital diagnosis and treatment to out-of-hospital health management is realized.

Described herein are methods and compositions for treatment of diabetes and / or obesity. Bitter oligopeptide molecules formulated for enteric delivery modulate signals involving receptors facing the lumen of the gastrointestinal tract, said signaling related hormones such as glucagon-like peptide-1 (GLP-1) and peptide tyrosine-tyrosine (PYY) that involve inhibition of gastric emptying and appetite. As a novel way to treat diabetes with limited adverse effects the described invention uses body's own endocrine system to treat diabetes, which is an advantage over current therapies that may simply provide disease management without cure or require more radical approaches such as surgical intervention.

The invention belongs to the technical field of biosensing, and particularly relates to a biosensor for detecting high-mobility group protein B1 as well as a preparation method and application of the biosensor. The biosensor is an organic electrochemical transistor and comprises a substrate; the source electrode, the drain electrode and the gate electrode are arranged on the substrate; an organic semiconductor channel connecting the source electrode and the drain electrode; the nucleic acid aptamer molecular layer is fixed on the surface of the gate electrode and can be specifically combined with HMGB1; the sealing agent molecular layer is used for passivating uncombined sites on the surface of the gate electrode; and when the HMGB1 is combined with the aptamer, electrolyte ions are caused to be doped into an organic semiconductor channel, so that the output current is efficiently modulated, and rapid, high-sensitivity and high-specificity label-free electrical detection is realized. The biosensor is suitable for dynamic monitoring of HMGB1 in various diseases such as acute kidney injury and sepsis, and a novel tool is provided for disease early diagnosis and disease course management.