Evidence map›Paper›PMID 41602207›Full record

ArticleFrontiers in digital health2025

Merging multimodal digital biomarkers into "Digital Neuro Fingerprints" for precision neurology in dementias: the promise of the right treatment for the right patient at the right time in the age of AI.

Ioannis Tarnanas, Azizi Seixas, Martin Wyss, Panagiotis Vlamos, Arzu Çöltekin

Abstract read
In one paragraph

Article in Frontiers in digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Ioannis TarnanasDepartment of Psychiatry, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States.
Azizi SeixasThe Media and Innovation Lab, Department of Informatics and Health Data Sciences, University of Miami Miller School of Medicine, Miami, FL, United States.
Martin WyssBioinformatics and Human Electrophysiology Laboratory (BiHELab), Department of Informatics, Ionian University, Corfu, Greece.
Panagiotis VlamosBioinformatics and Human Electrophysiology Laboratory (BiHELab), Department of Informatics, Ionian University, Corfu, Greece.
Arzu ÇöltekinInstitute of Interactive Technologies, School of Computer Science, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Brugg-Windisch, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Digital biomarkers are revolutionizing medicine in ways that were unimaginable a few years ago. Consequently, precision medicine approaches now realistically can promise personalization, i.e., the right treatments for the right patients at the right time, including earlier, targeted interventions which lead to a major paradigm shift in how medicine is practiced from reactive to preventive action. Although the scientific evidence is clear on the power of digital biomarkers, there is an unmet need for translating these findings into actionable insights in clinical practice. In this paper, we focus on Alzheimer's disease and related dementias (ADRD), and how digital biomarkers could empower clinical decision making in its preclinical stages. We argue that a new all-encompassing score is needed, akin to a BrainHealth Index linked to the established and validated risk stratifications frameworks and is directed at the prevention of ADRD. Specifically, we propose the new concept "Digital Neuro Fingerprint (DNF)", built with simultaneous collection of multimodal digital biomarkers (speech, gait, eye movements etc.) from smartphone based augmented reality or virtual reality while an individual is immersed in activities of daily living. Fusing the captured multimodal digital biomarkers, data is automatically analyzed with custom combinations of machine- and deep-learning approaches and enhanced with explainable artificial intelligence (XAI) and uncertainty quantifications. We argue that DNF is useful for capturing ADRD progression and should supersede the biomarkers that are invasive and expensive to obtain, offering a sensitive and highly specific score that measures meaningful aspects of health for the patients in high-frequency intervals.

Indexed as

Alzheimer's diseasebiomarkersdementiadigital biomarkersdigital healthprecision medicine

Identifiers

PMID41602207
PMCPMC12832889

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.