Machine learning in diagnosing coronary artery disease via optical pumped magnetometer magnetocardiography: a prospective cohort study.

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Title: Machine learning in diagnosing coronary artery disease via optical pumped magnetometer magnetocardiography: a prospective cohort study.
Authors: Tu C; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Yang S; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Wang Z; Department of Ultrasound, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, People's Republic of China.; Precision and Intelligent Imaging Laboratory, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, People's Republic of China., Liu L; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Ma Z; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Zhang H; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Feng L; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Cai B; Department of Medicine, Beijing X-Magtech Technologies Limited, No. 27, Middle Jiancaicheng Road, Haidian District, Beijing 100096, People's Republic of China., Zhang H; Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Advanced Innovation Center for Big Data-based Precision Medicine, Capital Medical University, No. 10 Youanmenwai Xitoutiao, Fengtai District, Beijing 100069, People's Republic of China.; Beijing Lab for Cardiovascular Precision Medicine, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China., Ding M; School of Instrumentation and Optoelectronic Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, People's Republic of China., Song X; Department of Cardiology, Beijing Anzhen Hospital, Capital Medical University, No. 2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.; Beijing Institute of Heart, Lung and Blood Vessel Diseases, No.2, Anzhen Road, Chaoyang District, Beijing 100029, People's Republic of China.
Source: Physiological measurement [Physiol Meas] 2025 Aug 11; Vol. 46 (8). Date of Electronic Publication: 2025 Aug 11.
Publication Type: Journal Article; Research Support, Non-U.S. Gov't
Journal Info: Publisher: IOP Pub. Ltd Country of Publication: England NLM ID: 9306921 Publication Model: Electronic Cited Medium: Internet ISSN: 1361-6579 (Electronic) Linking ISSN: 09673334 NLM ISO Abbreviation: Physiol Meas Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1361-6579
DOI:10.1088/1361-6579/adf0be