Comparison of machine learning algorithms for predicting cognitive impairment using neuropsychological tests
According to the results, the RF algorithm was the best classification model for both two- and three-way classification among the seven algorithms trained on an imbalanced NPTs SNSB dataset. The trained models proved useful for diagnosing MCI and ADD in patients with normal NPTs. These models can optimize cognitive evaluation, enhance diagnostic accuracy, and reduce missed diagnoses.
Authors
- Young Chul Youn (ORCID: https://orcid.org/0000-0002-2742-1759)
- Chanda Simfukwe (ORCID: https://orcid.org/0000-0003-2845-8016)
- Seong Soo An (ORCID: https://orcid.org/0000-0003-0385-2105)
Institutions
- Gachon University (KR)
- Chung-Ang University (KR)
Publication Details
- Journal
- Applied Neuropsychology Adult
- Published
- 2024-09-09
- DOI
- https://doi.org/10.1080/23279095.2024.2392282
- Citations
- 1
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.39
Funders
- National Research Foundation of Korea