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Deep Learning-Based Early Prediction of Syncope Onset During Tilt Table Testing via Temporal Convolutional Autoencoder Anomaly Detector.

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Bibliographic Details
Title: Deep Learning-Based Early Prediction of Syncope Onset During Tilt Table Testing via Temporal Convolutional Autoencoder Anomaly Detector.
Authors: Wong AW; Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, 43000, Petaling Jaya, Selangor, Malaysia., Chin WJ; Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, 43000, Petaling Jaya, Selangor, Malaysia., Tan MP; Ageing and Age-Associated Disorders Research Group, Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia., Mok SY; Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, 43000, Petaling Jaya, Selangor, Malaysia., Goh CH; Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, 43000, Petaling Jaya, Selangor, Malaysia. gohch@utar.edu.my.
Source: Annals of biomedical engineering [Ann Biomed Eng] 2026 May 19. Date of Electronic Publication: 2026 May 19.
Publication Type: Journal Article
Journal Info: Publisher: Springer Science + Business Media Country of Publication: United States NLM ID: 0361512 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-9686 (Electronic) Linking ISSN: 00906964 NLM ISO Abbreviation: Ann Biomed Eng Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1573-9686
DOI:10.1007/s10439-026-04176-9