Addictions

Applications of machine learning in addiction studies: A systematic review.

This study aims to provide a systematic review of the applications of machine learning methods in ad...

Novel Machine Learning Identifies Brain Patterns Distinguishing Diagnostic Membership of Human Immunodeficiency Virus, Alcoholism, and Their Comorbidity of Individuals.

The incidence of alcohol use disorder (AUD) in human immunodeficiency virus (HIV) infection is twice...

Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions.

IMPORTANCE: Current approaches to identifying individuals at high risk for opioid overdose target ma...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of ...

Rehab-Net: Deep Learning Framework for Arm Movement Classification Using Wearable Sensors for Stroke Rehabilitation.

In this paper, we present a deep learning framework "Rehab-Net" for effectively classifying three up...

Deep Learning-Based Prediction of Drug-Induced Cardiotoxicity.

Blockade of the human ether-à-go-go-related gene (hERG) channel by small molecules induces the prolo...

Addiction Theories and Constructs: a new series.

Predicting inadequate postoperative pain management in depressed patients: A machine learning approach.

Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to ...

Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Use of prescription opioids and problems of abuse and addiction have increased over the past decade....

Machine learning for prediction of sustained opioid prescription after anterior cervical discectomy and fusion.

BACKGROUND CONTEXT: The severity of the opioid epidemic has increased scrutiny of opioid prescribing...

Machine learning vs addiction therapists: A pilot study predicting alcohol dependence treatment outcome from patient data in behavior therapy with adjunctive medication.

BACKGROUND AND OBJECTIVES: Clinical staff providing addiction treatment predict patient outcome poor...

Physical characteristics not psychological state or trait characteristics predict motion during resting state fMRI.

Head motion (HM) during fMRI acquisition can significantly affect measures of brain activity or conn...

Binomial Logistic Regression and Artificial Neural Network Methods to Classify Opioid-Dependent Subjects and Control Group Using Quantitative EEG Power Measures.

Logistic regression (LR) and artificial neural networks (ANNs) are widely referred approaches in med...

Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models.

OBJECTIVE: Relapse rates are consistently high for stimulant user disorders. In order to obtain prog...

Support vector machine-based multivariate pattern classification of methamphetamine dependence using arterial spin labeling.

Arterial spin labeling (ASL) magnetic resonance imaging has been widely applied to identify cerebral...

Sex Differences in Nociceptin/Orphanin FQ Peptide Receptor-Mediated Pain and Anxiety Symptoms in a Preclinical Model of Post-traumatic Stress Disorder.

Nociceptin/Orphanin FQ (N/OFQ) is a neuropeptide that modulates pain transmission, learning/memory, ...

Antimicrobial Characteristics of Lactic Acid Bacteria Isolated from Homemade Fermented Foods.

. Lactic acid bacteria (LAB) were isolated from fermented foods, such as glutinous rice dough, corn ...

Machine-learning prediction of adolescent alcohol use: a cross-study, cross-cultural validation.

BACKGROUND AND AIMS: The experience of alcohol use among adolescents is complex, with international ...

Quantitative analysis of desomorphine in blood and urine using solid phase extraction and gas chromatography-mass spectrometry.

Desomorphine, a semi-synthetic opioid, is a component of the street drug Krokodil. Despite continued...

Methodological Advances in the Study of Hidden Variables: A Demonstration on Clinical Alcohol Use Disorder Data.

Research in the domain of psychopathology has been hindered by hidden variables-variables that are i...

Application of Machine Learning Methods to Predict Non-Alcoholic Steatohepatitis (NASH) in Non-Alcoholic Fatty Liver (NAFL) Patients.

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease worldwide. N...