Artificial Intelligence-Based Early Prediction of Acute Respiratory Failure in the Emergency Department Using Biosignal and Clinical Data
Our AI model demonstrates high predictive accuracy and significant associations with clinical outcomes. Our AI model has the potential to promptly aid in triage decisions. Our study shows that using AI to analyze biosignals advances disease detection and prediction.
Authors
- Dukyong Yoon (ORCID: https://orcid.org/0000-0003-1635-8376)
- Yun Jung Jung (ORCID: https://orcid.org/0000-0002-8887-0881)
- Wou Young Chung (ORCID: https://orcid.org/0000-0002-5435-2787)
- Ji Eun Park (ORCID: https://orcid.org/0000-0002-3035-6353)
- Changho Han (ORCID: https://orcid.org/0000-0003-4121-5465)
Institutions
- Yonsei University (KR)
- Severance Hospital (KR)
- Yonsei University Health System (KR)
- Ajou University (KR)
Publication Details
- Journal
- Yonsei Medical Journal
- Published
- 2024-11-25
- DOI
- https://doi.org/10.3349/ymj.2024.0126
- Citations
- 4
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- Korea Medical Device Development Fund
- Ministry of Trade, Industry and Energy
- Ministry of Food and Drug Safety
- Korea Health Industry Development Institute
- Ministry of Science and ICT, South Korea