[HTML][HTML] Wearable artificial intelligence for anxiety and depression: sco** review

A Abd-Alrazaq, R AlSaad, S Aziz, A Ahmed… - Journal of Medical …, 2023 - jmir.org
Background Anxiety and depression are the most common mental disorders worldwide.
Owing to the lack of psychiatrists around the world, the incorporation of artificial intelligence …

Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression

A Abd-Alrazaq, R AlSaad, F Shuweihdi, A Ahmed… - NPJ Digital …, 2023 - nature.com
Given the limitations of traditional approaches, wearable artificial intelligence (AI) is one of
the technologies that have been exploited to detect or predict depression. The current …

[HTML][HTML] The role of machine learning in diagnosing bipolar disorder: sco** review

Z Jan, N Ai-Ansari, O Mousa, A Abd-Alrazaq… - Journal of medical …, 2021 - jmir.org
Background Bipolar disorder (BD) is the 10th most common cause of frailty in young
individuals and has triggered morbidity and mortality worldwide. Patients with BD have a life …

An insight into diagnosis of depression using machine learning techniques: a systematic review

S Bhadra, CJ Kumar - Current medical research and opinion, 2022 - Taylor & Francis
Background In this modern era, depression is one of the most prevalent mental disorders
from which millions of individuals are affected today. The symptoms of depression are …

Depress-DCNF: A deep convolutional neuro-fuzzy model for detection of depression episodes using IoMT

A Kumar, SR Sangwan, A Arora, VG Menon - Applied Soft Computing, 2022 - Elsevier
Discernible patterns of a person's daily activities can be utilized to detect behavioral
symptomatology of mental illness at early stages. Wearable Internet of Medical Things …

A review of detection techniques for depression and bipolar disorder

D Highland, G Zhou - Smart Health, 2022 - Elsevier
Depression and bipolar disorder are mood disorders affecting millions of people worldwide
that can have severe impacts on one's quality of life. Our ability to detect these illnesses is …

Unipolar and bipolar depression detection and classification based on actigraphic registration of motor activity using machine learning and uniform manifold …

M Zakariah, YA Alotaibi - Diagnostics, 2023 - mdpi.com
Modern technology frequently uses wearable sensors to monitor many aspects of human
behavior. Since continuous records of heart rate and activity levels are typically gathered …

Portable technologies for digital phenoty** of bipolar disorder: A systematic review

LF Saccaro, G Amatori, A Cappelli, R Mazziotti… - Journal of affective …, 2021 - Elsevier
Background Bias-prone psychiatric interviews remain the mainstay of bipolar disorder (BD)
assessment. The development of digital phenoty** promises to improve BD management …

[HTML][HTML] Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study

G Anmella, F Corponi, BM Li, A Mas… - JMIR mHealth and …, 2023 - mhealth.jmir.org
Background: Depressive and manic episodes within bipolar disorder (BD) and major
depressive disorder (MDD) involve altered mood, sleep, and activity, alongside …

Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data

DK Nguyen, CL Chan, AHA Li… - Health Informatics …, 2022 - journals.sagepub.com
In the modern world, with so much inherent stress, mental health disorders (MHDs) are
becoming more common in every country around the globe, causing a significant burden on …