{
  "abstract": "Typing dynamics are being investigated as a digital behavioral marker for Parkinson's disease (PD), but the cross-dataset reliability of typing-based classi ers remains uncertain. We evaluated four public datasets (475 par ticipants; 270 with PD and 205 controls) across 12 transfer directions using split conformal prediction targeting 90% marginal coverage. In all three pri mary directions, coverage was below the 0.90 target and the one-sided tests remained signi cant after Holm correction: 0.598 (95% CI, 0.4830.704) for Tappy[->]MIT, 0.850 (0.7880.899) for MIT[->]Tappy, and 0.732 (0.6840.777) for clinical[->]self-reported transfer. Discrimination and coverage did not con sistently change together: LightGBM had lower AUC than logistic regression in all 12 directions but higher coverage in 11, with larger prediction sets. Class-conditional coverage varied by target cohort: PD-conditional cover age was 0.214 for Tappy[->]MIT, whereas healthy-control coverage was 0.700 for MIT[->]Tappy and 0.627 for clinical[->]self-reported transfer. Recalibration with 9 and 18 labeled target participants raised the lower condence bound above 0.80 in the latter two directions; in Tappy[->]MIT, it remained below 0.80 even with 25 labels. Weighted conformal prediction yielded coverage of 0.9181.000 without target labels but returned the full label set for 86% 100% of participants. Stress tests did not reproduce the observed coverage patterns, and black-box shift estimation did not support pure label shift as the dominant explanation for Tappy[->]MIT. Evaluating typing dynamics as a digital marker for PD requires cross-dataset assessment of discrimination, marginal and class-conditional coverage, and recovery costs. Clinical screen ing utility has not been established.",
  "abstract_shown": true,
  "affiliations": [
    "Inner Mongolia University"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 5,
  "authors": [
    {
      "name": "H. Guang"
    },
    {
      "name": "Z. Zhang"
    },
    {
      "name": "J. Qu"
    },
    {
      "name": "J. Ma"
    },
    {
      "affs": [
        0
      ],
      "name": "J. Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7pywxnxjc37b5.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.11.04.26366890",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26366890v1.full",
  "id": "7pywxnxjc37b5",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26366890v1",
  "language": null,
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "health informatics"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26366890v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7pywxnxjc37b5.ris",
  "sources": [
    {
      "first_seen": "2026-11-07T00:20:58Z",
      "native_id": "10.64898/2026.11.04.26366890",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.11.04.26366890v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:health informatics",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "A Cross-Dataset Audit of Discrimination and Conformal Prediction Coverage in Keystroke-Based Parkinson's Disease Classi cation",
  "title_text": "A Cross-Dataset Audit of Discrimination and Conformal Prediction Coverage in Keystroke-Based Parkinson's Disease Classi cation",
  "type": "preprint",
  "updated_at": "2026-11-08T00:20:58Z",
  "url": "https://research.draconitic.com/paper/7pywxnxjc37b5",
  "venue": "medRxiv",
  "versions": []
}