Machine learning–guided feature selection and predictive model construction for attention-deficit/hyperactivity disorder
This study reveals potential candidate indicators of ADHD and establishes an interpretable, low-cost machine learning model based on routine clinical data, offering a promising tool for early screening and clinical decision support.
Authors
- Rui Fu
- Haojie Meng
- Xiaofen Xing (ORCID: https://orcid.org/0000-0002-0016-9055)
- Qianqi Liu (ORCID: https://orcid.org/0000-0003-0405-4682)
- Xu Wang (ORCID: https://orcid.org/0000-0003-3731-8939)
- Li Yang (ORCID: https://orcid.org/0000-0003-2750-7031)
- Songtao Li (ORCID: https://orcid.org/0000-0002-0903-8801)
Institutions
- Nanjing Children's Hospital (CN)
- Second Affiliated Hospital of Nanjing Medical University (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Frontiers in Psychiatry
- Published
- 2025-12-17
- DOI
- https://doi.org/10.3389/fpsyt.2025.1724359
- Primary Topic
- Attention Deficit Hyperactivity Disorder
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Nanjing Medical University