16 results about "Chronic condition" patented technology

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

Embodiments of the present invention generally relate to novel immunostimulatory compositions of use to stimulate non-specific immune responses in a subject. In certain embodiments, immunogenic compositions disclosed herein can be directed to use in the eye of a subject. In some embodiments, the immunogenic compositions disclosed herein enhance non-specific immune responses in the eye of a subject to treat or reduce the risk of onset of an eye condition. In other embodiments, compositions disclosed herein can be used to treat eye infections due to a microorganism, tumors of the eye, as well as, chronic wounds or infections of the eye. In some embodiments, immunogenic ocular formulations disclosed herein include combinations of agents for prolonged exposure to the eye for improved outcomes.

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

Disclosed are compositions and methods for treating cortical hyperexcitability and reversing stroke-induced changes in gene expression and protein expression. For example, the methods can comprise administering vandefitemcel to a region of the brain of a subject to reduce chronic cortical hyperexcitability in the subject. Also disclosed are methods and blood biomarker panels for assessing an efficacy of a stem cell treatment for a chronic condition caused by stroke.

The invention belongs to the technical field of nursing management, and particularly relates to a remote nursing management method and system based on data analysis, which can make up for the defects of the prior art by integrating multi-dimensional nursing data, carrying out deep intelligent analysis and realizing accurate early warning and dynamic scheme adjustment based on comprehensive evaluation, quantify intraday blood pressure fluctuation and improve the nursing efficiency. According to the method, the deviation between the actual blood pressure and the target value is fused, symptom feeling risk calculation is introduced, subjective symptoms are objectively and quantitatively processed, health risks caused by symptom combinations or key symptoms can be effectively recognized, and the accuracy of the health risk is improved. Through multi-dimensional data fusion, innovative risk assessment, a comprehensive effect scoring mechanism and an intelligent closed-loop management process, the defects of fragmentation, one-sided and static states of an existing remote nursing technology are effectively overcome; a more comprehensive, more intelligent and more accurate remote nursing management solution is provided for chronic disease patients, especially crowds needing long-term management such as hypertension.

The invention discloses a medical agent behavior driving method, system and device based on a time sequence and a medium, and relates to the technical field of medical agent behavior driving. The user executes the first-round recommended diagnosis and treatment action to obtain a state tag and updates the state tag to a user file. And calculating a recommendation weight of each candidate diagnosis and treatment action and performing second diagnosis and treatment action recommendation to form a behavior-driven closed loop, establishing a multi-dimensional evaluation index system to evaluate a diagnosis and treatment action recommendation result, and optimizing the recommendation weight of the diagnosis and treatment action according to an evaluation result. The diagnosis and treatment action recommendation and the actual physiological state of the patient can be synchronized in real time, and the recommended strategy is automatically adjusted according to the difference between acute and chronic conditions. And through autonomous optimization iteration of the clinical effect feedback driving action recommendation model and the medical knowledge base, outputting a diagnosis and treatment behavior sequence which accords with clinical logic and has continuous learning ability.

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

The invention discloses a human health real-time monitoring system and method based on a hydrogel flexible sensor, relates to the technical field of health monitoring, and aims to solve the problems of chronic disease patient dynamic and static state signal acquisition distortion and mode switching energy consumption caused by insufficient scene adaptability of a traditional rigid sensor. Comprising a human body motion state signal acquisition module used for acquiring various human body motion state signals by using a hydrogel flexible sensor and detecting whether the hydrogel flexible sensor is in a preset working scene state according to the human body motion state signals; the mode selection module is used for selecting an adaptive working mode from preset working modes of the hydrogel flexible sensor according to the human body motion state signal output by the human body motion state signal acquisition module; according to the hydrogel flexible sensor, the problem of signal distortion caused by scene misjudgment of a traditional sensor is directly solved through a biocompatibility curved surface fitting design of the hydrogel flexible sensor and in combination with pressure signal frequency characteristic analysis.

A system and method are provided for integrating real-time mobility and balance data with local assistance robots to enhance patient safety and care. The system collects mobility and balance data from a health-monitoring app and transmits it to a local assistance robot. Based on predefined thresholds, the robot dynamically shifts into a guardian mode, proactively assisting the user with verbal cues, physical stabilization, or emergency interventions. The robot employs machine learning to adapt to individual user behaviors, improving the accuracy of interventions over time. In guardian mode, the robot tracks mobility metrics in real time and provides personalized support, including fall prevention, assistance with walking, and emergency alerts. This integration ensures seamless communication between monitoring systems and robotic assistants, enabling immediate and autonomous responses to potential mobility risks. The invention offers improved safety, reduced fall risks, and personalized care for individuals with chronic conditions, mobility impairments, or advanced age.

The present specification discloses methods for delivering sustainable healthcare to a patient-population suffering from a chronic condition to improved healthcare outcomes. The disclosed methods comprises aligning stakeholders involved in delivering care to the patient-population based on common metrics of success; establishing an advance primary care team to liaison with the patient-population and a community where patient-population resides to facilitate a delivery of care program; identifying the patient-population by assessing one or more individuals suffering from the chronic condition by risk stratification parameters; and implementing a sustainable value-based payment scheme. The disclosed methods may further comprise a data management step that provides a data infrastructure that facilitates analysis and reporting to enable transparent data sharing of each patient-population member linked to outcomes and cost and / or a technology platform step that implements an interoperable and flexible healthcare framework that monitors delivery of care and healthcare outcome of each patient-population member.

A decision support method and system is provided for monitoring and treating pediatric obesity. Embodiments include generating obesity risk curves corresponding to obesity risk levels, for example, severe and morbid obesity risk levels. Generating obesity risk curves depends on predicting at least one health proxy such as, for example, spend data and chronic conditions. Generating severe obesity curves depends on an age-dependent multiplier. An obesity risk level is assigned to a target pediatric patient using the obesity risk curves dependent on the age-dependent multiplier. In some aspects, an intervening response is initiated based on the assigned obesity risk level.

A decision support method and system is provided for monitoring and treating pediatric obesity. Embodiments include generating obesity risk curves corresponding to obesity risk levels, for example, severe and morbid obesity risk levels. Generating obesity risk curves depends on predicting at least one health proxy such as, for example, spend data and chronic conditions. Generating severe obesity curves depends on an age-dependent multiplier. An obesity risk level is assigned to a target pediatric patient using the obesity risk curves dependent on the age-dependent multiplier. In some aspects, an intervening response is initiated based on the assigned obesity risk level.

Virus-Like Particles (VLPs) derived from the Parahepevirinae and the Orthohepevirinae, particularly Paslahepevirus balayani, which can cause acute hepatitis and chronic conditions in immunocompromised patients are disclosed. Compositions of VLPs comprising capsid proteins capable of assembly in cultured cells that may be purified, disassembled, and reassembled in the presence of other molecules suitable for use as therapeutic drug products to facilitate targeting and delivery of cargo molecules to specific cells or tissues, or as antigenic agents to stimulate responses to epitopes exposed on the surfaces of VLPs, and functional capsids comprising polypeptide sequences comprising amino acid substitutions, insertions, or deletions of amino acid encoded by a consensus of ORF2 genes, wherein variants have similar or enhanced properties compared to capsid polypeptides encoded by naturally-occurring viruses obtained from clinical or prototype Hepatitis E Viruses (HEV) are disclosed.

Disclosed are compositions and methods for treating cortical hyperexcitability and reversing stroke-induced changes in gene expression and protein expression. For example, the methods can comprise administering vandefitemcel to a region of the brain of a subject to reduce chronic cortical hyperexcitability in the subject. Also disclosed are methods and blood biomarker panels for assessing an efficacy of a stem cell treatment for a chronic condition caused by stroke.

A decision support method and system is provided for monitoring and treating pediatric obesity. Embodiments include generating obesity risk curves corresponding to obesity risk levels, for example, severe and morbid obesity risk levels. Generating obesity risk curves depends on predicting at least one health proxy such as, for example, spend data and chronic conditions. Generating severe obesity curves depends on an age-dependent multiplier. An obesity risk level is assigned to a target pediatric patient using the obesity risk curves dependent on the age-dependent multiplier. In some aspects, an intervening response is initiated based on the assigned obesity risk level.

This disclosure relates to technologies to aid in chronic condition relief without reliance upon medications. More particularly, this disclosure is directed to methods and systems for using conditioning and a scent profile including an olfactory trigger to help users manage chronic debilitating conditions such as chronic pain.