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Cocaine-Related Disorders

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PsyGeNET: a knowledge platform on psychiatric disorders and their genes.

Bioinformatics (Oxford, England)
UNLABELLED: PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric diseases and their associated genes. PsyGeNET is composed of a database and a web interface supporting data...

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

BMC bioinformatics
BACKGROUND: Neuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in hum...

Identifying cognitive deficits in cocaine dependence using standard tests and machine learning.

Progress in neuro-psychopharmacology & biological psychiatry
There is a growing need to address the variability in detecting cognitive deficits with standard tests in cocaine dependence (CD). The aim of the current study was to identify cognitive deficits by means of Machine Learning (ML) algorithms: Generaliz...

Computational Systems Pharmacology-Target Mapping for Fentanyl-Laced Cocaine Overdose.

ACS chemical neuroscience
The United States of America is fighting against one of its worst-ever drug crises. Over 900 people a week die from opioid- or heroin-related overdoses, while millions more suffer from opioid prescription addiction. Recently, drug overdoses caused by...

Cocaine-Induced Preference Conditioning: a Machine Vision Perspective.

Neuroinformatics
Existing work on drug-induced synaptic changes has shown that the expression of perineuronal nets (PNNs) at the cerebellar cortex can be regulated by cocaine-related memory. However, these studies on animals have mostly relied on limited manually-dri...

Proteome-Informed Machine Learning Studies of Cocaine Addiction.

The journal of physical chemistry letters
No anti-cocaine addiction drugs have been approved by the Food and Drug Administration despite decades of effort. The main challenge is the intricate molecular mechanisms of cocaine addiction, involving synergistic interactions among proteins upstrea...

Artificial intelligence-based analysis of behavior and brain images in cocaine-self-administered marmosets.

Journal of neuroscience methods
BACKGROUND: The sophisticated behavioral and cognitive repertoires of non-human primates (NHPs) make them suitable subjects for studies involving cocaine self-administration (SA) schedules. However, ethical considerations, adherence to the 3Rs princi...

A novel deep neural network approach to detect and monitor cocaine drug abuse.

Computers in biology and medicine
PURPOSE: Cocaine is one of the most commonly used drugs that may lead to physical and mental health problems. It is necessary to identify individuals having cocaine use disorder as early as possible to monitor them properly. The objective of this wor...