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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
Tarnanas I, Seixas A, Wyss M, Vlamos P, Çöltekin A.. Frontiers in digital health, 2026-01-12
Topic: Risk, prevention and care in population studies
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.
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APA 7th
Tarnanas, I., Seixas, A., Wyss, M., Vlamos, P., & Çöltekin, A. (2025). 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. Frontiers in digital health. https://doi.org/10.3389/fdgth.2025.1727707
Vancouver
Tarnanas I, Seixas A, Wyss M, Vlamos P, Çöltekin A. 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. Frontiers in digital health. 2025. doi:10.3389/fdgth.2025.1727707. PMID: 41602207.
BibTeX
@article{tarnanas2025-41602207,
author = {Tarnanas, I. and Seixas, A. and Wyss, M. and Vlamos, P. and Çöltekin, A.},
title = {{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}},
journal = {Frontiers in digital health},
year = {2025},
doi = {10.3389/fdgth.2025.1727707},
pmid = {41602207},
url = {https://doi.org/10.3389/fdgth.2025.1727707}
}
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Key findings
- 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.
Study details
- Evidence strengthLow
How this study scored 45/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it. We have no data on journal's citation record, times cited, citations per year, impact for its field and year, cited by studies here, still being cited, senior author's track record, institution's track record and multi-centre collaboration, so those were left out: it earned 26 of the 58 points we could judge it on, which is 45 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Frontiers in digital health) |
| Journal's citation record | — / 4 | No journal record from OpenAlex — left out of this score |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | — / 7 | No citation count (not found in OpenAlex) — left out of this score |
| Citations per year | — / 5 | No citation count or no year — left out of this score |
| Impact for its field and year | — / 6 | No field-weighted citation impact (OpenAlex has none yet) — left out of this score |
| Cited by studies here | — / 6 | Not yet checked against this library's citation graph — left out of this score |
| Still being cited | — / 4 | No yearly citation counts — left out of this score |
| Senior author's track record | — / 4 | Senior author's record not available — left out of this score |
| Institution's track record | — / 3 | No institution listed in OpenAlex — left out of this score |
| Multi-centre collaboration | — / 3 | Institutions not listed — left out of this score |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41602207) |
| Free to read | 2 / 2 | Free to read |
| Points | 26 / 58 | Scored on 11 of 20 parts. We have no data for the rest, so they are left out: 26 of the 58 points we could judge it on is 45 out of 100. |
| Total | 45 / 100 | — |
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