Machine learning-based system for predicting e.g. coronary artery disease, has user interface that is integrated with machine learning system to enable medical professionals and individuals, where machine learning module processes dataset of patient attributes
	BERNVAL H K; TYAGI A; CHAUHAN J
	2025-03-30
专利权人	BERNVAL H K (BERN-Individual) ; TYAGI A (TYAG-Individual) ; CHAUHAN J (CHAU-Individual) ; MEERUT ENG & TECHNOLOGY INST (MEER-Non-standard)
申请日期	2025-03-30
专利号	IN202511031445-A
成果简介	NOVELTY - The system has a machine learning module processing a dataset of patient attributes e.g. age, using a random forest algorithm optimized with a jellyfish feature selection algorithm. The module achieves a classification accuracy of 98.90 percent, and a user interface inputs data and displays prediction results. The user interface is implemented using a flask web framework, and enables real-time predictions on a multipage website. The jellyfish algorithm reduces the number of features to enhance model efficiency and prevent overfitting, and the algorithm uses 100 estimators. The user interface is integrated with machine learning (ML) system to enable medical professionals and individuals. USE - Machine learning-based system for predicting heart disease e.g. coronary artery disease and atrial fibrillation, in public health initiatives, for enabling large-scale screening of populations in underserved regions to identify at-risk individuals and optimizing resource allocation by clinicians, medical professionals and healthcare providers. ADVANTAGE - The system ensures optimizing feature selection and reducing computational complexity, so that the system offers a low-cost, efficient alternative to diagnostics, thus supporting clinical and individual use. The system provides clinicians with a reliable tool for early heart disease diagnosis, thus facilitating timely interventions for conditions such as coronary artery disease and atrial fibrillation, and hence allowing the remote patients to assess heart disease risk without requiring in-person medical consultations. The system enables large-scale screening of populations in underserved regions to identify at-risk individuals and optimize resource allocation. DETAILED DESCRIPTION - An INDEPENDENT CLAIM is also included for a method for predicting heart disease.
IPC 分类号	A61B-005/00 ; A61B-005/021 ; G16H-010/20 ; G16H-050/20 ; G16H-050/30
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/13321
专题	中国科学院新疆生态与地理研究所
作者单位	1.BERNVAL H K (BERN-Individual) 2.TYAGI A (TYAG-Individual) 3.CHAUHAN J (CHAU-Individual) 4.MEERUT ENG & TECHNOLOGY INST (MEER-Non-standard)
推荐引用方式 GB/T 7714	BERNVAL H K,TYAGI A,CHAUHAN J. Machine learning-based system for predicting e.g. coronary artery disease, has user interface that is integrated with machine learning system to enable medical professionals and individuals, where machine learning module processes dataset of patient attributes. IN202511031445-A[P]. 2025.

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