Interpretable machine learning models for predicting cognitive impairment using NHANES neuropsychological tests: nutritional and sociodemographic associations.
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| Title: | Interpretable machine learning models for predicting cognitive impairment using NHANES neuropsychological tests: nutritional and sociodemographic associations. |
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| Authors: | Song L; Department of Neurology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China., Li C; Department of Neurology, The First Affiliated Hospital Of Chongqing Medical University, Chongqing Key Laboratory of Major Neurological and Mental Disorders, Chongqing Key Laboratory of Neurology, Chongqing, China., Xiang X; Department of Nuclear Medicine, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, China., Lin P; Department of Otolaryngology Head and Neck Surgery, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Children and Adolescents' Health and Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China. |
| Source: | Frontiers in nutrition [Front Nutr] 2026 Jan 14; Vol. 12, pp. 1680290. Date of Electronic Publication: 2026 Jan 14 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S. A Country of Publication: Switzerland NLM ID: 101642264 Publication Model: eCollection Cited Medium: Print ISSN: 2296-861X (Print) Linking ISSN: 2296861X NLM ISO Abbreviation: Front Nutr Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2296-861X |
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| DOI: | 10.3389/fnut.2025.1680290 |
