{
  "abstract": "Background: Community health check-ups routinely collect non-cognitive data. Whether these support mild cognitive impairment (MCI) triage, and whether machine learning outperforms regression, is unclear. Methods: Cross-sectional analysis of 2650 community-dwelling adults aged ≥ 65 in Akita, Japan (2018-2025). MCI was defined by the NCGG-FAT (1.5 SD, age/education-adjusted norms). Thirty-four pre-specified non-cognitive predictors were modelled using tree ensembles, penalised regression, other machine-learning families and simple reference scores, with stratified 70/30 splitting, DeLong tests, 100 repeated splits, training-derived thresholds, calibration metrics and decision-curve analysis. Results: MCI prevalence was 28.6%. Random forest discriminated best (ROC AUC 0.722, 95% CI 0.681-0.761; PR-AUC 0.542) and was well calibrated (slope 1.048; intercept -0.024), but its advantage over LASSO regression was marginal (ΔAUC +0.031, p = 0.044) and absent versus gradient boosting (p = 0.059). All multivariable models greatly outperformed the Kihon Checklist (AUC 0.550, p < 0.001). Neither operating point was deployable: at 0.5, sensitivity was 0.269 (166/227 cases missed); at the training-derived Youden threshold (0.321), sensitivity was 0.604, specificity 0.699, and PPV 0.445. Net benefit exceeded assess-all/assess-none between threshold probabilities 0.15-0.60. Conclusions: Routine non-cognitive data support moderate, well-calibrated MCI discrimination, but machine learning added little over regression. This is an exploratory triage aid requiring external validation.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Occupational Therapy, Graduate School of Medicine, Akita University, 1-1-1 Hondo, Akita 010-8543, Japan.",
    "Advanced Research Center for Geriatric and Gerontology, Akita University, 1-1-1 Hondo, Akita 010-8543, Japan.",
    "Clinical Research Promotion and Support Office, Future Cooperative Research Organization, Akita University, 1-1-1 Hondo, Akita 010-8543, Japan.",
    "Integrated Community Support Center, Public Health and Welfare Department, City Hall of Yokote, Yokote, Akita 010-8543, Japan.",
    "Omori Municipal Hospital, Yokote, Akita 010-8543, Japan."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Ayuto Kodama",
      "orcid": "0000-0002-2583-9422"
    },
    {
      "affs": [
        1
      ],
      "name": "Takako Ohnuma",
      "orcid": "0009-0000-2636-0301"
    },
    {
      "affs": [
        1
      ],
      "name": "Kana Sasaki",
      "orcid": "0009-0007-7508-8528"
    },
    {
      "affs": [
        1
      ],
      "name": "Kaoru Sugawara"
    },
    {
      "affs": [
        2
      ],
      "name": "Nobuhiro Fujiyama",
      "orcid": "0000-0001-9411-2254"
    },
    {
      "affs": [
        3
      ],
      "name": "Youko Umetsu"
    },
    {
      "affs": [
        4
      ],
      "name": "Tsuyoshi Ono"
    },
    {
      "affs": [
        1
      ],
      "name": "Hidetaka Ota",
      "orcid": "0000-0003-4815-3711"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3y5jxv1s4q4ft.bib",
  "cited_by": 0,
  "doi": "10.3390/geriatrics11050138",
  "fulltext_url": "https://europepmc.org/articles/PMC13704611",
  "id": "3y5jxv1s4q4ft",
  "issns": [
    "2308-3417"
  ],
  "landing_url": "https://europepmc.org/article/MED/42930017",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2738|Dementia and Cognitive Impairment Research"
    ]
  ],
  "openalex": "W7215056087",
  "pdf_url": "https://europepmc.org/articles/PMC13704611?pdf=render",
  "pmcid": "PMC13704611",
  "pmid": "42930017",
  "published": "2026-10-01",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3y5jxv1s4q4ft.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:01Z",
      "native_id": "MED:42930017",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42930017"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2738|Dementia and Cognitive Impairment Research",
      "subfield": "psychiatry"
    }
  ],
  "title": "Identifying Mild Cognitive Impairment from Routinely Collected Physical, Functional and Psychosocial Measures in Community-Dwelling Older Adults: A Comparative Machine-Learning and Regression Modelling Study in the Northern Japanese ORANGE Registry.",
  "title_text": "Identifying Mild Cognitive Impairment from Routinely Collected Physical, Functional and Psychosocial Measures in Community-Dwelling Older Adults: A Comparative Machine-Learning and Regression Modelling Study in the Northern Japanese ORANGE Registry.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:22:01Z",
  "url": "https://research.draconitic.com/paper/3y5jxv1s4q4ft",
  "venue": "Geriatrics (Basel, Switzerland)",
  "versions": []
}