Psychiatry

Addictions

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

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The use of machine learning improves the assessment of drug-induced driving behaviour.

RATIONALE: Car-driving performance is negatively affected by the intake of alcohol, tranquillizers, ...

Discrimination of alcohol dependence based on the convolutional neural network.

In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 rece...

Predicting alcohol dependence from multi-site brain structural measures.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance im...

Comparative study between deep learning and QSAR classifications for TNBC inhibitors and novel GPCR agonist discovery.

Machine learning is a well-known approach for virtual screening. Recently, deep learning, a machine ...

Artificial intelligence interventions focused on opioid use disorders: A review of the gray literature.

BACKGROUND: With the artificial intelligence (AI) paradigm shift comes momentum toward the developme...

Data enhanced Hammett-equation: reaction barriers in chemical space.

It is intriguing how the Hammett equation enables control of chemical reactivity throughout chemical...

Alcoholic liver disease: A registry view on comorbidities and disease prediction.

Alcoholic-related liver disease (ALD) is the cause of more than half of all liver-related deaths. Su...

Investigation of MDMA Inhibitory Effect on CytochromeP450 3A4 in Isolated Perfused Rat Liver Model Using Tramadol.

MDMA (methylenedioxymethamphetamine) is a synthetic compound, which is a structurally derivative of...

Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of al...

Machine learning approach to predict postoperative opioid requirements in ambulatory surgery patients.

Opioids play a critical role in acute postoperative pain management. Our objective was to develop ma...

Modeling motivation for alcohol in humans using traditional and machine learning approaches.

Given the significant cost of alcohol use disorder (AUD), identifying risk factors for alcohol seeki...

Ontological model of multi-agent Smart-system for predicting drug properties based on modified algorithms of artificial immune systems.

BACKGROUND: Currently, due to the huge progress in the field of information technologies and compute...

Predictors of emergency department opioid administration and prescribing: A machine learning approach.

INTRODUCTION: The opioid epidemic has altered normative clinical perceptions on addressing both acut...

Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study.

OBJECTIVE: To develop and validate a machine-learning algorithm to improve prediction of incident OU...

Robotic Versus Open Ureteroneocystostomy: Is There a Robotic Benefit?

We sought to compare the outcomes of patients who underwent an open robotic ureteroneocystostomy f...

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