Psychiatry

Addictions

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

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Effectiveness of Machine Learning-Based Adjustments to an eHealth Intervention Targeting Mild Alcohol Use.

INTRODUCTION: This study aimed to evaluate effects of three machine learning based adjustments made ...

How to enhance employee engagement in the AI era: An fsQCA-based study.

BackgroundThe ongoing fourth industrial revolution, characterized by the integration of intelligent ...

Application of machine learning to identify risk factors for outpatient opioid prescriptions following spine surgery.

INTRODUCTION: Spine surgery is a common source of narcotic prescriptions and carries potential for l...

Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction.

BACKGROUND: Opioid addiction is a worldwide public health crisis. In the United States, for example,...

Hybrid contrastive multi-scenario learning for multi-task sequential-dependence recommendation.

Multi-scenario and multi-task learning are crucial in industrial recommendation systems to deliver h...

Machine learning based on alcohol drinking-gut microbiota-liver axis in predicting the occurrence of early-stage hepatocellular carcinoma.

BACKGROUND: Alcohol drinking and gut microbiota are related to hepatocellular carcinoma (HCC), but t...

Precision Opioid Prescription in ICU Surgery: Insights from an Interpretable Deep Learning Framework.

PURPOSE: Appropriate opioid management is crucial to reduce opioid overdose risk for ICU surgical pa...

Multi-scale region selection network in deep features for full-field mammogram classification.

Early diagnosis and treatment of breast cancer can effectively reduce mortality. Since mammogram is ...

The Development and Validation of an Artificial Intelligence Chatbot Dependence Scale.

In recent years, a plethora of artificial intelligence (AI) chatbots have been developed and made av...

Barley Grain Proteome Assessment Using Multi-Environment Trial Data and Machine Learning.

Proteomics can be used to assess individual protein abundances, which could reflect genotypic and en...

Predicting the Risk of Driving Under the Influence of Alcohol Using EEG-Based Machine Learning.

Driving under the influence of alcohol (DUIA) is closely associated with alcohol use disorder (AUD)....

Teaching deep networks to see shape: Lessons from a simplified visual world.

Deep neural networks have been remarkably successful as models of the primate visual system. One cru...

Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.

Feature selection is essentially the process of picking informative and relevant features from a lar...

Developing a Wearable Sensor-Based Digital Biomarker of Opioid Dependence.

BACKGROUND: Repeated opioid exposure leads to a variety of physiologic adaptations that develop at d...

Spatial patterns of rural opioid-related hospital emergency department visits: A machine learning analysis.

As opioid-related overdose emergency department visits continue to rise in the United States, there ...

Factors predicting access to medications for opioid use disorder for housed and unhoused patients: A machine learning approach.

BACKGROUND: Opioid use disorder (OUD) is a growing public health crisis, with opioids involved in an...

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