AI Medical Compendium Topic

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Mental Disorders

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An adaptive data-driven architecture for mental health care applications.

PeerJ
BACKGROUND: In the current era of rapid technological innovation, our lives are becoming more closely intertwined with digital systems. Consequently, every human action generates a valuable repository of digital data. In this context, data-driven arc...

Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis.

Neuroscience and biobehavioral reviews
Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising pre...

Diagnostic machine learning applications on clinical populations using functional near infrared spectroscopy: a review.

Reviews in the neurosciences
Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides ...

A deep learning quantification of patient specificity as a predictor of session attendance and treatment response to internet-enabled cognitive behavioural therapy for common mental health disorders.

Journal of affective disorders
BACKGROUND: Increasing an individual's ability to focus on concrete, specific detail, thus reducing the tendency toward overly broad, decontextualised generalisations about the self and world, is a target within cognitive behavioural therapy (CBT). H...

Bridging the Skills Gap: Evaluating an AI-Assisted Provider Platform to Support Care Providers with Empathetic Delivery of Protocolized Therapy.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Despite the high prevalence and burden of mental health conditions, there is a global shortage of mental health providers. Artificial Intelligence (AI) methods have been proposed as a way to address this shortage, by supporting providers with less ex...

Evaluation of deep learning-based depression detection using medical claims data.

Artificial intelligence in medicine
Human accuracy in diagnosing psychiatric disorders is still low. Even though digitizing health care leads to more and more data, the successful adoption of AI-based digital decision support (DDSS) is rare. One reason is that AI algorithms are often n...

Arts therapies for mental disorders in COVID-19 patients: a comprehensive review.

Frontiers in public health
BACKGROUND AND OBJECTIVE: The COVID-19 global pandemic has necessitated the urgency for innovative mental health interventions. We performed a comprehensive review of the available literature on the utility and efficacy of arts therapies in treating ...

Psychological factors underlying attitudes toward AI tools.

Nature human behaviour
What are the psychological factors driving attitudes toward artificial intelligence (AI) tools, and how can resistance to AI systems be overcome when they are beneficial? Here we first organize the main sources of resistance into five main categories...