AIMC Topic: Substance-Related Disorders

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Comparison of hepatitis B and SARS-CoV2 vaccination rates in people who attended Drugs and Addiction Centres.

Frontiers in public health Jan 16, 2024
BACKGROUND AND AIMS: Persons with substance use disorder are at increased risk for hepatitis B virus (HBV) infection. Although most of them are attached to social health centers, the vaccination rate in this group is low. In this context, we designed...
Vaccination Retrospective Studies SARS-CoV-2 Substance-Related Disorders Hepatitis B Vaccines Hepatitis B RNA, Viral Humans COVID-19
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Drug Use and Artificial Intelligence: Weighing Concerns and Possibilities for Prevention.

American journal of preventive medicine Dec 4, 2023
Humans Artificial Intelligence Substance-Related Disorders
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A relational agent for treating substance use in adults: Protocol for a randomized controlled trial with a psychoeducational comparator.

Contemporary clinical trials Feb 20, 2023
BACKGROUND: Substance use disorders (SUDs) are prevalent and compromise health and wellbeing. Scalable solutions, such as digital therapeutics, may offer a population-based strategy for addressing SUDs. Two formative studies supported the feasibility...
Adult Anxiety Disorders Randomized Controlled Trials as Topic Humans Robotics Substance-Related Disorders Social Interaction
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Predicting Substance Use Treatment Failure with Transfer Learning.

Substance use & misuse Sep 21, 2022
Transfer learning, which involves repurposing a trained model on a related task, may allow for better predictions with substance use data than models that are trained using the target data alone. This approach may also be useful for small clinical da...
Humans Neural Networks, Computer Machine Learning Databases, Factual Substance-Related Disorders Treatment Failure
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Long-term results after robot-assisted radical prostatectomy of a simplified inguinal hernia prevention technique without artificial substance use.

International journal of urology : official journal of the Japanese Urological Association Aug 24, 2022
INTRODUCTION: Durable techniques that prevent postoperative inguinal hernia (IH) after robot-assisted radical prostatectomy (RARP) have not been established. This study evaluated the long-term efficacy of a postoperative IH prevention technique that ...
Hernia, Inguinal Male Postoperative Complications Robotics Substance-Related Disorders Robotic Surgical Procedures Prostatectomy Humans Retrospective Studies
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A Bayesian mixed effects support vector machine for learning and predicting daily substance use disorder patterns.

The American journal of drug and alcohol abuse Feb 23, 2022
Substance use disorder (SUD) is a heterogeneous disorder. Adapting machine learning algorithms to allow for the parsing of intrapersonal and interpersonal heterogeneity in meaningful ways may accelerate the discovery and implementation of clinically...
Humans Female Male Bayes Theorem Support Vector Machine Substance-Related Disorders
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Predicting changes in substance use following psychedelic experiences: natural language processing of psychedelic session narratives.

The American journal of drug and alcohol abuse Jun 5, 2021
: Experiences with psychedelic drugs, such as psilocybin or lysergic acid diethylamide (LSD), are sometimes followed by changes in patterns of tobacco, opioid, and alcohol consumption. But, the specific characteristics of psychedelic experiences that...
Lysergic Acid Diethylamide Psilocybin Surveys and Questionnaires Emotions Natural Language Processing Substance-Related Disorders Hallucinogens Alcohol Drinking Female Adult Male Humans
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Analyzing Online Reviews of Substance Use Disorder Treatment Facilities in the USA Using Machine Learning.

Journal of general internal medicine Mar 16, 2021
Substance-Related Disorders Humans Machine Learning United States
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Predicting hospital readmission in patients with mental or substance use disorders: A machine learning approach.

International journal of medical informatics Apr 18, 2020
OBJECTIVE: Mental or substance use disorders (M/SUD) are major contributors of disease burden with high risk for hospital readmissions. We sought to develop and evaluate a readmission model using a machine learning (ML) approach.
Patient Discharge Patient Readmission ROC Curve Longitudinal Studies Substance-Related Disorders Adolescent Child Female Risk Factors Hospitalization Mental Disorders Retrospective Studies Male Middle Aged Comorbidity Aged Young Adult Adult Humans Machine Learning
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Machine-Learning prediction of comorbid substance use disorders in ADHD youth using Swedish registry data.

Journal of child psychology and psychiatry, and allied disciplines Apr 1, 2020
BACKGROUND: Children with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs.
Humans Machine Learning Sweden Risk Factors Substance-Related Disorders Registries Attention Deficit Disorder with Hyperactivity Adolescent Child, Preschool Child Cross-Sectional Studies Comorbidity
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