{
  "abstract": "Background: Mild cognitive impairment (MCI) is a clinically heterogeneous syndrome that can represent an early manifestation of neurodegenerative disease. Diagnosis relies on assessments that are difficult to scale, leaving many individuals unidentified. Methods: In this cross-sectional study conducted in the United States, Australia, and Spain between May 2022 and October 2024, 638 adults aged ≥ 50 years were classified as cognitively unimpaired (CU; n = 441) or MCI (n = 197) using Petersen/NIA-AA criteria. Participants completed a self-administered, tablet-based assessment (Altoida NeuroMarker Platform) integrating motor, speech, and augmented reality tasks. An XGBoost classifier was trained to distinguish CU from MCI. Diagnostic performance, test-retest reliability, and convergent validity were evaluated. Findings: Median assessment time was 13.8 min. Participants reported comfort with digital technology (67%), willingness to engage in cognitive screening (90%), and positive usability. Altoida’s NeuroMarker differentiated MCI with ROC-AUC 0.90, 95% CI 0.88–0.92 and comparable performance in an independent cohort (ROC-AUC 0.87, 95% CI 0.80–0.93; n = 75). Cognitive composite and domain scores were lower in MCI than in CU. Classifier agreement across repeated assessments was κ = 0.60, and reliability of composite and domain scores was moderate-to-good (ICC 0.55–0.80). The composite score correlated with the Mini-Mental State Examination (MMSE) ( r s = 0.40, p < 0.001) and Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Total Index ( r s = 0.58, p < 0.001). The platform also showed convergent validity of cognitive domains (| r s | = 0.27–0.50, p < 0.001). Interpretation: A brief, self-administered multimodal assessment identified clinically adjudicated MCI and demonstrated convergent validity, test-retest reliability, and consistent performance in an independent cohort. Prospective studies should evaluate its implementation in real-world workflows. Funding: Alzheimer’s Drug Discovery Foundation ; Altoida Inc.",
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  "author_total": 24,
  "authors": [
    {
      "name": "M. Florencia Iulita",
      "orcid": "0000-0002-3360-4498"
    },
    {
      "name": "Vijaya B. Kolachalama"
    },
    {
      "name": "Victoria Brugada-Ramentol"
    },
    {
      "name": "John Harrison"
    },
    {
      "name": "Nicholas Griffin"
    },
    {
      "name": "Gonzalo Sánchez Benavides"
    },
    {
      "name": "Elena Vera-Campuzano"
    },
    {
      "name": "Carolina Minguillon"
    },
    {
      "name": "Daniel Alcolea",
      "orcid": "0000-0002-3819-3245"
    },
    {
      "name": "Lucy Mackintosh",
      "orcid": "0000-0003-4746-2598"
    },
    {
      "name": "Larry Ward"
    },
    {
      "name": "Adria Tort Merino",
      "orcid": "0000-0002-5646-0482"
    },
    {
      "name": "Mircea Balasa",
      "orcid": "0000-0002-1795-4228"
    },
    {
      "name": "Sahoko Ishida"
    },
    {
      "name": "Oriol Grau Rivera"
    },
    {
      "name": "Marc Suarez Calvet",
      "orcid": "0000-0002-2993-569X"
    },
    {
      "name": "Joanne Robertson"
    },
    {
      "name": "James Doecke",
      "orcid": "0000-0003-2863-0293"
    },
    {
      "name": "Claudia Porta Mas",
      "orcid": "0009-0006-3982-1772"
    },
    {
      "name": "Silvia Fallone"
    },
    {
      "name": "Mylea Charvat"
    },
    {
      "name": "Ioannis Tarnanas",
      "orcid": "0000-0003-4069-6551"
    },
    {
      "name": "Marc Jones"
    },
    {
      "name": "Emmanuel Streel"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/fepa27b51j0dm.bib",
  "cited_by": 0,
  "doi": "10.1016/j.eclinm.2026.104266",
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  "language": "en",
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  "pmcid": "PMC13720161",
  "pmid": "42964515",
  "published": "2026-10-23",
  "publisher": "Elsevier BV",
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  "title": "A multimodal digital NeuroMarker platform with composite and domain-level validity for identification of mild cognitive impairment: a cross-sectional study",
  "title_text": "A multimodal digital NeuroMarker platform with composite and domain-level validity for identification of mild cognitive impairment: a cross-sectional study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-03T12:21:06Z",
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