Artificial intelligence driven predictive toxicology and side effects analysis system for drug safety and risk assessment, has patient monitoring and data collection node provided with TI MSP432 board connected with power supply, IMU Sensor and ECG Sensor
	KAUR M
	2025-03-29
专利权人	UNIV GALGOTIAS (UYGA-Non-standard)
申请日期	2025-03-29
专利号	IN202511031225-A
成果简介	NOVELTY - The system has a patient monitoring and data collection node provided with a TI MSP432 board (56) connected with a power supply (51), an IMU Sensor (52), an ECG Sensor (53), an infrared Thermometer (54), a pulse oximeter (55), and an SX1276 module (57). The patient monitoring and data collection node enables real-time acquisition of vital health parameters and seamless wireless transmission for continuous monitoring of drug effects on patients. An adverse event reporting and data logging node ensures automated adverse drug reaction reporting by capturing patient feedback, verifies prescriptions, and monitors environmental conditions. USE - Artificial intelligence (AI) driven predictive toxicology and side effects analysis system for drug safety and risk assessment. ADVANTAGE - The system ensures seamless communication between nodes using efficient data transmission technology, thus facilitating real-time analysis and decision-making. The system enhances pharmacovigilance, optimizes drug safety assessment, and minimizes health risks associated with adverse drug reactions. The power supply ensures uninterrupted monitoring by providing the necessary energy for the system's operation. DESCRIPTION OF DRAWING(S) - The drawing shows a block diagram of an AI-driven predictive toxicology and side effects analysis system for drug safety and risk assessment. 51Power supply 52IMU Sensor 53ECG Sensor 54Infrared Thermometer 55Pulse oximeter 56TI MSP432 board 57SX1276 module
IPC 分类号	A61B-005/00 ; A61B-005/0205 ; A61B-005/08 ; A61B-005/1455 ; G16H-040/67
国家	印度
专业领域	信息技术
语种	英语
成果类型	专利
文献类型	科技成果
条目标识符	http://119.78.100.226:8889/handle/3KE4DYBR/13368
专题	中国科学院新疆生态与地理研究所
作者单位	UNIV GALGOTIAS (UYGA-Non-standard)
推荐引用方式 GB/T 7714	KAUR M. Artificial intelligence driven predictive toxicology and side effects analysis system for drug safety and risk assessment, has patient monitoring and data collection node provided with TI MSP432 board connected with power supply, IMU Sensor and ECG Sensor. IN202511031225-A[P]. 2025.

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