Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study.

Saved in:
Bibliographic Details
Title: Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study.
Authors: Chen GY; Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan., Lu SC; Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan., Cheng WH; Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan., Gao JW; Department of Emergency Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan., Sun JT; Department of Emergency Medicine, Far Eastern Memorial Hospital, New Taipei City, Taiwan., Huang CH; Department of Emergency Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan., Tsai CL; Department of Emergency Medicine, National Taiwan University Hospital, National Taiwan University College of Medicine, Taipei, Taiwan. chulintsai@ntuh.gov.tw., Fu LC; Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei, Taiwan. lichen@ntu.edu.tw.; Department of Computer Science and Information Engineering, National Taiwan University, CSIE Der Tian Hall, No. 1, Section 4, Roosevelt Road, Taipei, 106319, Taiwan. lichen@ntu.edu.tw.
Source: BioData mining [BioData Min] 2026 Jul 08. Date of Electronic Publication: 2026 Jul 08.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101319161 Publication Model: Print-Electronic Cited Medium: Print ISSN: 1756-0381 (Print) Linking ISSN: 17560381 NLM ISO Abbreviation: BioData Min
Database: MEDLINE Ultimate
Description
ISSN:1756-0381
DOI:10.1186/s13040-026-00583-9