Machine learning applied to digital phenoty**: A systematic literature review and taxonomy

MP dos Santos, WF Heckler, RS Bavaresco… - Computers in Human …, 2024 - Elsevier
Health conditions, encompassing both physical and mental aspects, hold an influence that
extends beyond the individual. These conditions affect personal well-being, relationships …

Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine

F Stolfi, H Abreu, R Sinella, S Nembrini… - Frontiers in …, 2024 - frontiersin.org
Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the
third leading cause of disability worldwide. In MDD, several factors can simultaneously …

Digital phenoty** in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology

JM Lipschitz, S Lin, S Saghafian… - Acta Psychiatrica …, 2024 - Wiley Online Library
Background Effective treatment of bipolar disorder (BD) requires prompt response to mood
episodes. Preliminary studies suggest that predictions based on passive sensor data from …

[HTML][HTML] Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning

YG Rykov, KP Ng, MD Patterson, BA Gangwar… - Computers in Biology …, 2024 - Elsevier
Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild
cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable …

Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number

F Corponi, BM Li, G Anmella, A Mas… - Translational …, 2024 - nature.com
Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited
specialized care availability remains a major bottleneck thus hindering pre-emptive …

Bipolar disorders: an update on critical aspects

V Oliva, G Fico, M De Prisco, X Gonda… - The Lancet Regional …, 2025 - thelancet.com
Bipolar disorders are chronic psychiatric conditions characterized by recurrent episodes of
mania and depression. Affecting over 1% of the global population, these disorders …

Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting

G Anmella, A Mas, M Sanabra… - Journal of Affective …, 2024 - Elsevier
Background Bipolar disorder (BD) lacks objective measures for illness activity and treatment
response. Electrodermal activity (EDA) is a quantitative measure of autonomic function …

Sleep–wake variations of electrodermal activity in bipolar disorder

C Valenzuela‐Pascual, A Mas, R Borràs… - Acta Psychiatrica …, 2025 - Wiley Online Library
Background Affective states influence the sympathetic nervous system, inducing variations
in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) …

Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): Protocol for a pragmatic …

G Anmella, F Corponi, BM Li, A Mas, M Garriga… - BJPsych Open, 2024 - cambridge.org
BackgroundBipolar disorder is highly prevalent and consists of biphasic recurrent mood
episodes of mania and depression, which translate into altered mood, sleep and activity …

A Bayesian analysis of heart rate variability changes over acute episodes of bipolar disorder

F Corponi, BM Li, G Anmella… - npj Mental Health …, 2024 - nature.com
Bipolar disorder (BD) involves autonomic nervous system dysfunction, detectable through
heart rate variability (HRV). HRV is a promising biomarker, but its dynamics during acute …