Uncovering predictors of bipolar II conversion to bipolar I: A machine learning analysis of national health records in Taiwan
Our findings highlight the utility of machine learning in stratifying BD-II patients at elevated risk for BD-I conversion, offering a data-driven framework to support early clinical intervention and personalized care.
Authors
- André F. Carvalho (ORCID: https://orcid.org/0000-0002-2500-5671)
- Kuo‐Chuan Hung (ORCID: https://orcid.org/0000-0002-4507-8085)
- Chih‐Sung Liang (ORCID: https://orcid.org/0000-0003-1138-5586)
- Yang‐Chieh Brian Chen (ORCID: https://orcid.org/0000-0003-0622-9175)
- Liang‐Jen Wang (ORCID: https://orcid.org/0000-0002-5320-1151)
- Chih‐Wei Hsu (ORCID: https://orcid.org/0000-0002-8650-4060)
- Chien‐Yuan Chen (ORCID: https://orcid.org/0000-0003-2831-8822)
- Mu-Hong Chen
- Eduard Vieta
Institutions
- Barwon Health (AU)
- Deakin University (AU)
- Chang Gung University (TW)
- Taipei Veterans General Hospital (TW)
- Kaohsiung Chang Gung Memorial Hospital (TW)
- Chi Mei Medical Center (TW)
- National Defense Medical Center (TW)
- Universitat de Barcelona (ES)
- The University of Texas Health Science Center at Houston (US)
Publication Details
- Journal
- Journal of Affective Disorders
- Published
- 2025-10-23
- DOI
- https://doi.org/10.1016/j.jad.2025.120518
- Citations
- 1
- Primary Topic
- Bipolar Disorder and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.47