AI Medical Compendium Topic

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Mental Disorders

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Validation of a generative artificial intelligence tool for the critical appraisal of articles on the epidemiology of mental health: Its application in the Middle East and North Africa.

Journal of epidemiology and population health
Mental health disorders have a high disability-adjusted life years in the Middle East and North Africa. This rise has led to a surge in related publications, prompting researchers to use AI tools like ChatGPT to reduce time spent on routine tasks. Ou...

Classification of Neuropsychiatric Disorders via Brain-Region-Selected Graph Convolutional Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
For the classification of patients with neuropsychiatric disorders based on rs-fMRI data, this paper proposed a Brain-Region-Selected graph convolutional network (BRS-GCN). In order to effectively identify the most significant biomarkers associated w...

Trade-offs between machine learning and deep learning for mental illness detection on social media.

Scientific reports
Social media platforms provide valuable insights into mental health trends by capturing user-generated discussions on conditions such as depression, anxiety, and suicidal ideation. Machine learning (ML) and deep learning (DL) models have been increas...

Exploring mental health literacy on twitter: A machine learning approach.

Journal of affective disorders
OBJECTIVES: This study investigates whether reducing mental illness stigma, enhancing help-seeking efficacy, and maintaining positive mental health mediate the relationship between the recognition of mental disorders and help-seeking attitudes.

Fast and effective assessment for individuals with special needs form optimization and prediction models.

BMC psychology
The aim of this study was to determine which items in the psychological assessment forms used by counselling and research centres for individuals with special needs are effective in classifying individuals into special needs diagnostic categories. Da...

Machine learning based identification of suicidal ideation using non-suicidal predictors in a university mental health clinic.

Scientific reports
Suicide causes over 700,000 deaths annually worldwide. Mental disorders are closely linked to suicidal ideation, but predicting suicide remains complex due to the multifaceted nature of contributing factors. Traditional assessment tools often fail to...

Mental health practitioners' perceptions and adoption intentions of AI-enabled technologies: an international mixed-methods study.

BMC health services research
BACKGROUND: As mental health disorders continue to surge, exceeding the capacity of available therapeutic resources, the emergence of technologies enabled by artificial intelligence (AI) offers promising solutions for supporting and delivering patien...

Mental disorder preventing by worry levels detection in social media using deep learning based on psycho-linguistic features: application on the COVID-19 lockdown period.

Computers in biology and medicine
BACKGROUND: The COVID-19 pandemic has had a profound effect on the daily routines of individuals and has influenced various facets of society, including healthcare systems, economy, education, and more. With lockdown and social distancing measures, p...

Smartphone digital phenotyping in mental health disorders: A review of raw sensors utilized, machine learning processing pipelines, and derived behavioral features.

Psychiatry research
With increased access to digital technology, there has been a surge in the use of and interest in digital phenotyping as a tool to calculate various features from raw smart device data. However, the increased usage of digital phenotyping has created ...

An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion.

Scientific reports
Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental health illnesses due to their subjective and complicated nature. In this work, we offer an innovative...