7 results about "Patient profile" patented technology

A drug administration management method according to one embodiment disclosed herein may comprise the steps of: receiving identification information of a first drug from a pharmacist terminal; transmitting permission information corresponding to the identification information of the first drug to the pharmacist terminal; receiving customized medication guidance, in which the permission information is personalized according to patient profile information of a patient, from the pharmacist terminal, and storing the customized medication guidance in a patient information database; receiving identification information of a drug from a patient terminal and searching for the identification information of the drug in an internal database; and generating a customized administration schedule for the patient according to administration schedule information of the first drug included in the customized medication guidance if the searched identification information of the drug is the identification information of the first drug.

This invention discloses a method, system, and medium for dynamic prediction of pregnancy complications in SLE patients, belonging to the field of medical information technology. It aims to solve the technical problems of existing risk assessment methods, such as the inability to effectively integrate multi-dimensional time-series data and the lack of causal mechanism analysis of the dynamic evolution of risk, resulting in biased, delayed, and clinically inoperable prediction results. The method includes the following steps: S1: Acquiring multimodal health data of the target patient during pregnancy as a time series; S2: Based on the multimodal health data, constructing and updating a dynamic patient profile reflecting the patient's psychosocial state, immune inflammatory activity, and target organ function; S3: Inputting the dynamic patient profile into a trained risk prediction model. This invention, by constructing a dynamic patient profile and employing a time-series deep learning model for risk prediction, achieves a comprehensive, dynamic, and mechanistically transparent risk assessment of pregnancy complications in SLE patients.

Systems and methods for multimodal monitoring of physiological conditions are disclosed. The systems include a sensor hub that can detect a presence of sensor devices in its environment. The sensor devices are configured to sense a parameter relevant to patient fluid inflow or outflow. The sensor hub associates at least a subset of the detected sensor devices with a patient profile and determines parameters relevant to patient fluid inflow or outflow that the associated sensor devices are capable of sensing. Based on the determined parameters, the sensor hub enters a mode of multimodal monitoring, activates sensor streams from the associated sensor devices in accordance with the mode of multimodal monitoring, establishes a secured communication channel with a patient medical record system, and transmits an update to the patient medical record system based on data received from the sensor streams.

This invention relates to the technical field of radiotherapy information management, and more specifically, to an intelligent management system and method for the entire radiotherapy process. The system includes shelves, a mobile device, a transport device, a docking station, a cleaning mechanism, a radiotherapy information system program, and a radiotherapy storage management system program. The radiotherapy information system program is used to create patient files, and the radiotherapy storage management system program is used to manage and automatically transport radiotherapy molds. By incorporating the mobile device, transport device, docking station, cleaning mechanism, a radiotherapy information system program capable of creating patient files and sending outbound instructions, and a radiotherapy storage management system program with lifecycle management algorithms, order priority algorithms, and storage location allocation algorithms, this invention enables the entire process from admission and file creation, mold storage and retrieval, treatment execution to final cleaning, without requiring the patient to handle the molds personally.

The present application relates to the field of medical health information technology, and discloses a blood lipid health management system based on hospitalization indexes and food image recognition, which comprises a patient file grabbing module, a health risk reminding module, a personalized blood lipid target setting module, a food image recognition scanning module, a blood lipid index correlation calculation module, a health index analysis module and a blood lipid health visualization management module. Through deep integration of automatic grabbing of hospital diagnosis and treatment data and food image recognition AI technology outside the hospital, a continuous blood lipid risk dynamic monitoring and intervention closed loop is formed throughout the hospital, a three-dimensional quantitative evaluation model of daily blood lipid intake compliance Ge, blood lipid standard reaching prediction value Ys and blood vessel health comprehensive score Qc is constructed, dynamic correlation calculation of diet behavior, medication compliance and blood lipid biochemical indexes and blood vessel ultrasound structure indexes is realized, and decision basis for hierarchical intervention is provided for medical staff, so as to improve blood lipid standard reaching rate and patient self-management ability.

This invention discloses a method and system for autism assessment using near-infrared spectral imaging and eye-tracking, relating to the field of autism risk assessment technology. The key technical points include the following steps: collecting the age, developmental level, and past medical history of suspected autism patients to generate autism patient profiles; establishing personal information files; collecting near-infrared spectral imaging data and eye-tracking data of the patients; screening abnormal correlation data of potential autism pathological features to obtain correlation data to be assessed; extracting the functional coupling characteristics, temporal synchronization, and intensity attenuation patterns of abnormal correlations in the correlation data to be assessed; and determining whether it is necessary to perform scheme fusion processing on the correlation data to be assessed from different testing schemes based on the functional coupling characteristics and temporal synchronization. The effect is that it effectively captures the specific pathological characteristics of patients, avoids the problem of a uniform testing paradigm masking individual differences, and further improves the accuracy and specificity of the assessment.

This invention discloses a remote monitoring and risk correction system for pediatric infusion drip rate based on hierarchical medical treatment, belonging to the field of monitoring and automated control technology. It includes: a data acquisition module that acquires image sequences of the infusion vessel, vibration sequences, patient's body acceleration sequences, drug solution environmental parameters, and medical order background data, and generates a patient profile vector; a fusion estimation module that outputs the original drip rate estimation sequence; a compensation module that generates body motion influencing factors and, combined with drug solution environmental parameters, generates accurate corrected drip rate data through fluid-structure interaction calculations; an inference module that constructs a medical risk graph structure and uses the body motion influencing factors to dynamically recalibrate edge weights, outputting a real-time risk score; and a decision module that inputs the risk score, accurate corrected drip rate, and body motion influencing factors into a pre-trained reinforcement learning model, retrieves the optimal adjustment step size, and outputs corrective control commands. This invention achieves precise monitoring and adaptive risk control of pediatric infusions.