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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 …
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
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 …
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
Background Effective treatment of bipolar disorder (BD) requires prompt response to mood
episodes. Preliminary studies suggest that predictions based on passive sensor data from …
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
Neuropsychiatric symptoms (NPS) and mood disorders are common in individuals with mild
cognitive impairment (MCI) and increase the risk of progression to dementia. Wearable …
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
Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited
specialized care availability remains a major bottleneck thus hindering pre-emptive …
specialized care availability remains a major bottleneck thus hindering pre-emptive …
Bipolar disorders: an update on critical aspects
Bipolar disorders are chronic psychiatric conditions characterized by recurrent episodes of
mania and depression. Affecting over 1% of the global population, these disorders …
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 …
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) …
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 …
BackgroundBipolar disorder is highly prevalent and consists of biphasic recurrent mood
episodes of mania and depression, which translate into altered mood, sleep and activity …
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
Bipolar disorder (BD) involves autonomic nervous system dysfunction, detectable through
heart rate variability (HRV). HRV is a promising biomarker, but its dynamics during acute …
heart rate variability (HRV). HRV is a promising biomarker, but its dynamics during acute …