Integrating Heart Rate Variability Improves Machine Learning-based Prediction of Panic Disorder Symptom Severity
Our findings demonstrate that integrating HRV with psychometric scales improves machine learning-based prediction of PD severity. We also highlighted LF as a promising variable among HRV components.
Authors
- J. Lee
- Changbae Bang (ORCID: https://orcid.org/0000-0001-6244-7666)
- Jooyoung Oh (ORCID: https://orcid.org/0000-0001-6721-399X)
- Jeong‐Ho Seok (ORCID: https://orcid.org/0000-0002-9402-7591)
- Jae‐Jin Kim (ORCID: https://orcid.org/0000-0002-1395-4562)
- Eun Joo Kim (ORCID: https://orcid.org/0000-0003-3061-2051)
- Byung-Hoon Kim (ORCID: https://orcid.org/0000-0003-2501-038X)
Institutions
- Yonsei University (KR)
- Eulji University (KR)
Publication Details
- Journal
- Clinical Psychopharmacology and Neuroscience
- Published
- 2025-03-25
- DOI
- https://doi.org/10.9758/cpn.24.1261
- Citations
- 1
- Primary Topic
- Heart Rate Variability and Autonomic Control
- Type
- article
- Field-Weighted Citation Impact
- 1.39
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea