Barcelona snapshots

Prof. Maria Faurholt-Jepsen

Maria Faurholt-Jepsen psiquiatra Controversies Psiquiatria Barcelona
Psychiatric Center Copenhagen, Rigshospitalet, Dinamarca
Ponència Marcadors digitals i intel·ligència artificial: la solució definitiva
Data Divendres, 21 d'abril, 2023
Hora 12:00 - 12:45
Taula rodona 2 Diagnòstic de precisió en psiquiatria: aconseguirem canviar de model?

BIOGRAFIA

Maria Faurholt-Jepsen is medical doctor, DMSc and assistant professor with a research focus on electronic monitoring in Bipolar Disorder.

She has conducted many studies regarding smartphones -including four large RCT’s- through the last decade with a main focus on the use of smartphones for monitoring and treatment within bipolar disorder.

She is author or co-author of over 100 peer-reviewed articles in international journals receiving 3700 citations. (H index 34).

https://pubmed.ncbi.nlm.nih.gov/?term=Faurholt-Jepsen+M&cauthor_id=30610400

RESUM

Digital health technology is promising for improving mental healthcare by enabling continuous monitoring of behaviour by smartphones and wearables, new paradigms for testing in virtual reality, and analysis of big data through machine learning for prediction models. This might advance prevention efforts and contribute to diagnostics and treatment. This presentation will show examples from studies using digital markers collected primarily from smartphones in patients with bipolar disorder.

REFERÈNCIES

[Full paper] John Torous, ..., Faurholt-Jepsen M, et al. (2021). The growing field of digital psychiatry: current evidence and the future of apps, social media, chatbots, and virtual reality. World Psychiatry. 2021 Oct;20(3):318-335

[Full paper] Faurholt-Jepsen M, et al. (2021). Voice analyses using smartphone-based data in patients with bipolar disorder, unaffected relatives and healthy control individuals, and during different affective states. Int J Bipolar Disord. 2021 Dec 1;9(1):38

Faurholt-Jepsen M, et al. (2022). Discriminating between patients with unipolar disorder, bipolar disorder, and healthy control individuals based on voice features collected from naturalistic smartphone calls. Acta Psychiatr Scand. 2022 Mar;145(3):255-267.

[Full paper] Faurholt-Jepsen M, et al. (2022). Differences in mobility patterns according to machine learning models in patients with bipolar disorder and patients with unipolar disorder. J Affect Disord. 2022 Jun 1;306:246-253