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Mental Disorders

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Artificial Intelligence and the Future of Psychiatry.

IEEE pulse
An estimated 792 million people live with mental health disorders worldwide-more than one in ten people-and this number is expected to grow in the shadow of the Coronavirus disease 2019 (COVID-19) pandemic. Unfortunately, there aren't enough mental h...

"Sorry I Didn't Hear You." The Ethics of Voice Computing and AI in High Risk Mental Health Populations.

AJOB neuroscience
This article examines the ethical and policy implications of using voice computing and artificial intelligence to screen for mental health conditions in low income and minority populations. Mental health is unequally distributed among these groups, w...

Imputation and characterization of uncoded self-harm in major mental illness using machine learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias.

Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

JAMA psychiatry
IMPORTANCE: Suicide is a public health problem, with multiple causes that are poorly understood. The increased focus on combining health care data with machine-learning approaches in psychiatry may help advance the understanding of suicide risk.

Quantifying the Association Between Psychotherapy Content and Clinical Outcomes Using Deep Learning.

JAMA psychiatry
IMPORTANCE: Compared with the treatment of physical conditions, the quality of care of mental health disorders remains poor and the rate of improvement in treatment is slow, a primary reason being the lack of objective and systematic methods for meas...

Convolutional neural network model to predict causal risk factors that share complex regulatory features.

Nucleic acids research
Major progress in disease genetics has been made through genome-wide association studies (GWASs). One of the key tasks for post-GWAS analyses is to identify causal noncoding variants with regulatory function. Here, on the basis of >2000 functional fe...

[Artificial intelligence and nursing care: reflections in psychiatry].

Soins; la revue de reference infirmiere
A key government priority, artificial intelligence (IA) in healthcare is a real opportunity for nursing professionals. Faced with the daily difficulties encountered, AI could bring a new perspective to nursing care in psychiatry and free up time for ...

[Corpus Analysis of Psychiatric Disorders Utilizing Natural Language Processing and Neurolinguistics].

Brain and nerve = Shinkei kenkyu no shinpo
Natural language processing (NLP) is a technology in which a computer processes human "natural language" directly. Along with the development of technologies such as automatic morphological analysis and transition words or sentences to vectors, more ...

Randomized controlled trial of an online machine learning-driven risk assessment and intervention platform for increasing the use of crisis services.

Journal of consulting and clinical psychology
OBJECTIVE: Mental illness is a leading cause of disease burden; however, many barriers prevent people from seeking mental health services. Technological innovations may improve our ability to reach underserved populations by overcoming many existing ...

Digital Interventions for Mental Disorders: Key Features, Efficacy, and Potential for Artificial Intelligence Applications.

Advances in experimental medicine and biology
Mental disorders are highly prevalent and often remain untreated. Many limitations of conventional face-to-face psychological interventions could potentially be overcome through Internet-based and mobile-based interventions (IMIs). This chapter intro...