Psychiatry

Addictions

Latest AI and machine learning research in addictions for healthcare professionals.

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A deep learning-based system for automatic detection of emesis with high accuracy in Suncus murinus.

Quantifying emesis in Suncus murinus (S. murinus) has traditionally relied on direct observation or ...

Biopsychosocial based machine learning models predict patient improvement after total knee arthroplasty.

Total knee arthroplasty (TKA) is an effective treatment for end stage osteoarthritis. However, biops...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use dis...

Eye-tracking dataset of endoscopist-AI teaming during colonoscopy: Retrospective and real-time acquisition.

Recent studies have demonstrated that integrating AI into colonoscopy procedures significantly impro...

Machine learning research methods to predict postoperative pain and opioid use: a narrative review.

The use of machine learning to predict postoperative pain and opioid use has likely been catalyzed b...

A deep learning analysis for dual healthcare system users and risk of opioid use disorder.

The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Adminis...

K-nearest neighbor algorithm for imputing missing longitudinal prenatal alcohol data.

AIMS: The objective of this study is to illustrate the application of a machine learning algorithm, ...

A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.

PURPOSE OF REVIEW: Artificial intelligence (AI) offers a new frontier for aiding in the management o...

Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis.

This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-trau...

A machine learning-based model for predicting the risk of cognitive frailty in elderly patients on maintenance hemodialysis.

Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frail...

Development of deep learning auto-encoder algorithms for predicting alcohol use in Korean adolescents based on cross-sectional data.

Alcohol is a highly addictive substance, presenting significant global public health concerns, parti...

Partial directed coherence analysis of resting-state EEG signals for alcohol use disorder detection using machine learning.

INTRODUCTION: Excessive alcohol consumption negatively impacts physical and psychiatric health, life...

Spatial Craving Patterns in Marijuana Users: Insights From fMRI Brain Connectivity Analysis With High-Order Graph Attention Neural Networks.

The excessive consumption of marijuana can induce substantial psychological and social consequences....

Analyzing Secondary Cancer Risk: A Machine Learning Approach.

OBJECTIVE: Addressing the rising cancer rates through timely diagnosis and treatment is crucial. Add...

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