Psychiatry

Addictions

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

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Predicting the Hallucinogenic Potential of Molecules Using Artificial Intelligence.

The development of new drugs addressing serious mental health and other disorders should avoid the p...

Uncertainty quantification in neural-network based pain intensity estimation.

Improper pain management leads to severe physical or mental consequences, including suffering, a neg...

Improving treatment completion for young adults with substance use disorder: Machine learning-based prediction algorithms.

Substance use disorder (SUD) treatment completion was intertwined with various factors. However, few...

The Relationship Between Metal Exposure and HPV Infection: Evidence from Explainable Machine Learning Methods.

HPV is a ubiquitous pathogen implicated in cervical and other cancers. Although vaccines are availab...

Anxiety in young people: Analysis from a machine learning model.

The study addresses the detection of anxiety symptoms in young people using artificial intelligence ...

Gut microbiota-based machine-learning signature for the diagnosis of alcohol-associated and metabolic dysfunction-associated steatotic liver disease.

Alcoholic-associated liver disease (ALD) and metabolic dysfunction-associated steatotic liver diseas...

Machine Learned Classification of Ligand Intrinsic Activities at Human μ-Opioid Receptor.

Opioids are small-molecule agonists of μ-opioid receptor (μOR), while reversal agents such as naloxo...

Antiferromagnetic artificial neuron modeling of the withdrawal reflex.

Replicating neural responses observed in biological systems using artificial neural networks holds s...

Machine learning and deep learning approaches for enhanced prediction of hERG blockade: a comprehensive QSAR modeling study.

BACKGROUND: Cardiotoxicity is a major cause of drug withdrawal. The hERG channel, regulating ion flo...

Deep Learning Used with a Colorimetric Sensor Array to Detect Indole for Nondestructive Monitoring of Shrimp Freshness.

Intelligent colorimetric freshness indicator is a low-cost way to intuitively monitor the freshness ...

Quantifying the pollution changes and meteorological dependence of airborne trace elements coupling source apportionment and machine learning.

Airborne trace elements (TEs) present in atmospheric fine particulate matter (PM) exert notable thre...

Imputation of label-free quantitative mass spectrometry-based proteomics data using self-supervised deep learning.

Imputation techniques provide means to replace missing measurements with a value and are used in alm...

Self-help groups and opioid use disorder treatment: An investigation using a machine learning-assisted robust causal inference framework.

OBJECTIVES: This study investigates the impact of participation in self-help groups on treatment com...

Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.

BACKGROUND AND AIMS: Opioid use disorder (OUD) and opioid dependence lead to significant morbidity a...

Video-based automatic hand hygiene detection for operating rooms using 3D convolutional neural networks.

Hand hygiene among anesthesia personnel is important to prevent hospital-acquired infections in oper...

Prediction of sustained opioid use in children and adolescents using machine learning.

BACKGROUND: Opioid misuse in the paediatric population is understudied. This study aimed to develop ...

Opioid Nonadherence Risk Prediction of Patients with Cancer-Related Pain Based on Five Machine Learning Algorithms.

OBJECTIVES: Opioid nonadherence represents a significant barrier to cancer pain treatment efficacy. ...

Machine Learning Identification of Nutrient Intake Variations across Age Groups in Metabolic Syndrome and Healthy Populations.

This study undertakes a comprehensive examination of the intricate link between diet nutrition, age,...

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