Psychiatry

Prediction of Suicidal Thoughts and Suicide Attempts in People Who Gamble Based on Biological-Psychological-Social Variables: A Machine Learning Study.

Recent research has shown that people who gamble are more likely to have suicidal thoughts and attem...

Development of machine-learning-driven signatures for diagnosing and monitoring therapeutic response in major depressive disorder using integrated immune cell profiles and plasma cytokines.

Diagnosis and treatment efficacy of major depressive disorder (MDD) currently lack stable and relia...

QSPR modeling to predict surface tension of psychoanaleptic drugs using the hybrid DA-SVR algorithm.

A robust Quantitative Structure-Property Relationship (QSPR) model was presented to predict the surf...

Exploring potential ADHD biomarkers through advanced machine learning: An examination of audiovisual integration networks.

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition marked by inattent...

Resting-State Electroencephalogram Depression Diagnosis Based on Traditional Machine Learning and Deep Learning: A Comparative Analysis.

The global prevalence of Major Depressive Disorder (MDD) is increasing at an alarming rate, undersco...

Medical diagnosis based on artificial intelligence and decision support system in the management of health development.

BACKGROUND: Medical diagnosis plays a critical role in our daily lives. Every day, over 10 billion c...

3D CNN for neuropsychiatry: Predicting Autism with interpretable Deep Learning applied to minimally preprocessed structural MRI data.

Predictive modeling approaches are enabling progress toward robust and reproducible brain-based mark...

Generative artificial intelligence (GenAI) and decision-making: Legal & ethical hurdles for implementation in mental health.

This article argues that significant risks are being taken with using GenAI in mental health that sh...

GO-MAE: Self-supervised pre-training via masked autoencoder for OCT image classification of gynecology.

Genitourinary syndrome of menopause (GSM) is a physiological disorder caused by reduced levels of oe...

Evaluation of neonatal nurses' anxiety and readiness levels towards the use of artificial intelligence.

OBJECTIVEC: This is a cross-sectional and descriptive study to determine the levels of artificial in...

Autism Spectrum Disorder and Atypical Brain Connectivity: Novel Insights from Brain Connectivity-Associated Genes by Combining Random Forest and Support Vector Machine Algorithm.

It is estimated that approximately one in every 100 children is diagnosed with autism spectrum disor...

Investigating the impact of an AI-based play activities intervention on the quality of life of school-aged children with ADHD.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disord...

[Can artificial intelligence help prevent suicide in healthcare workers?].

Identification of cultural conversations in therapy using natural language processing models.

Researchers have historically focused on understanding therapist multicultural competency and orient...

Predicting maintenance lithium response for bipolar disorder from electronic health records-a retrospective study.

BACKGROUND: Optimising maintenance drug treatment selection for people with bipolar disorder is chal...

Haves and have-nots: socioeconomic position improves accuracy of machine learning algorithms for predicting high-impact chronic pain.

Lower socioeconomic position (SEP) is associated with increased risk of developing chronic pain, exp...

Federated learning-based prediction of depression among adolescents across multiple districts in China.

Depression in adolescents is a serious mental health condition that can affect their emotional and s...

Federated learning and deep learning framework for MRI image and speech signal-based multi-modal depression detection.

Adolescence is a significant period for developing skills and knowledge and learning about managing ...

Building and testing of a robotic intervention framework to enhancing the social engagement of children with autism spectrum disorder.

PURPOSE: Humanoid robot intervention programmes for children with autism spectrum disorder (ASD) are...

Predicting remission after acute phase pharmacotherapy in patients with bipolar I depression: A machine learning approach with cross-trial and cross-drug replication.

OBJECTIVES: Interpatient variability in bipolar I depression (BP-D) symptoms challenges the ability ...

Peripheral Blood Mononuclear Cell Biomarkers for Major Depressive Disorder: A Transcriptomic Approach.

Major depressive disorder (MDD) is a complex condition characterized by persistent depressed mood, ...