A review of machine learning and deep learning approaches on mental health diagnosis

NK Iyortsuun, SH Kim, M Jhon, HJ Yang, S Pant - Healthcare, 2023 - mdpi.com
Combating mental illnesses such as depression and anxiety has become a global concern.
As a result of the necessity for finding effective ways to battle these problems, machine …

Clinical prediction models in psychiatry: a systematic review of two decades of progress and challenges

AJ Meehan, SJ Lewis, S Fazel, P Fusar-Poli… - Molecular …, 2022 - nature.com
Recent years have seen the rapid proliferation of clinical prediction models aiming to
support risk stratification and individualized care within psychiatry. Despite growing interest …

[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review

R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …

Modern views of machine learning for precision psychiatry

ZS Chen, IR Galatzer-Levy, B Bigio, C Nasca, Y Zhang - Patterns, 2022 - cell.com
In light of the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC),
the advent of functional neuroimaging, novel technologies and methods provide new …

The role of the oral microbiota related to periodontal diseases in anxiety, mood and trauma-and stress-related disorders

M Martínez, TT Postolache, B García-Bueno… - Frontiers in …, 2022 - frontiersin.org
The prevalence of anxiety, mood and trauma-and stress-related disorders are on the rise;
however, efforts to develop new and effective treatment strategies have had limited success …

Applications of artificial intelligence− machine learning for detection of stress: a critical overview

AFA Mentis, D Lee, P Roussos - Molecular Psychiatry, 2024 - nature.com
Psychological distress is a major contributor to human physiology and pathophysiology, and
it has been linked to several conditions, such as auto-immune diseases, metabolic …

Development and validation of a machine learning prediction model of posttraumatic stress disorder after military deployment

S Papini, SB Norman, L Campbell-Sills, X Sun… - JAMA network …, 2023 - jamanetwork.com
Importance Military deployment involves significant risk for life-threatening experiences that
can lead to posttraumatic stress disorder (PTSD). Accurate predeployment prediction of …

[HTML][HTML] At-home, telehealth-supported ketamine treatment for depression: Findings from longitudinal, machine learning and symptom network analysis of real-world …

DS Mathai, TD Hull, L Vando, M Malgaroli - Journal of affective disorders, 2024 - Elsevier
Background Improving safe and effective access to ketamine therapy is of high priority given
the growing burden of mental illness. Telehealth-supported administration of sublingual …

[HTML][HTML] Integrated analysis of proteomics, epigenomics and metabolomics data revealed divergent pathway activation patterns in the recent versus chronic post …

S Muhie, A Gautam, B Misganaw, R Yang… - Brain, behavior, and …, 2023 - Elsevier
Metabolomics, proteomics and DNA methylome assays, when done in tandem from the
same blood sample and analyzed together, offer an opportunity to evaluate the molecular …

The link between post-traumatic stress disorder and systemic lupus erythematosus

L Goldschen, J Ellrodt, HL Amonoo… - Brain, behavior, and …, 2023 - Elsevier
Systemic lupus erythematosus (SLE) is a heterogeneous, multisystem autoimmune disorder
characterized by unpredictable disease flares. Although the pathogenesis of SLE is …