Precision psychiatry
The organising idea of this whole ecosystem: moving psychiatric assessment and monitoring from coarse, episodic, subjective judgement toward measurement that is earlier, lower-burden, repeatable, and clinically interpretable — without replacing the clinician.
Why now
Precision psychiatry is becoming increasingly relevant as AI and digital technologies make it possible to combine speech, behavioural, questionnaire-based, and clinical data for earlier and more individualised detection of mental-health risks. This matters particularly given growing demand for mental-health care among children, adolescents and elderly people, while psychiatric services are often overloaded.
Low-cost, privacy-preserving tools — such as short structured speech tasks or tablet-based assessments — could support early screening, triage, longitudinal monitoring, and more timely referral.
The seven perspectives this ecosystem connects
| Perspective | Represented by |
|---|---|
| Biological / immunological / registry-, biobank- and omics-informed | Michael E. Benros |
| Clinical psychiatry: BPD, psychotherapy process, social cognition, emotion regulation | Zsolt Unoka |
| Neurolinguistics: temporal characteristics of spontaneous speech | Gábor Gosztolya, Speech Gap |
| Multimodal AI in structured clinical interaction | Bruno Melício, multimodal behaviour analysis |
| Translational case | Argus Cognitive |
| Avatar and human–AI interaction | Avatar therapy, NIPG |
| Innovation and viability | Erik Szabó |
An eighth thread closes the set: the information structure backing research, development and test phases using AI technologies — which is what this wiki itself is.
The five dimensions that must stay separate
A recurring discipline throughout this wiki. A claim about one is never a claim about another:
- Clinical validity — does the measurement track what it claims to track?
- Clinical utility — does using it change decisions or outcomes?
- Intellectual property — who owns what, and on what terms?
- Regulatory status — what is it permitted to be used for, and under which framework?
- Commercial readiness — could it be sold, supported and adopted?
The broader aim
Build an ecosystem connecting basic research, well-specified data collection, reproducible analysis, clinical validation, and protectable or deployable diagnostic, monitoring and therapeutic support methods.
Related pages
Overview · Longitudinal within-person measurement · Clinical AI translation · Capability readiness · INNOFAIR workshop programme