AIMC Topic: Alcoholism

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Decoding diagnosis and lifetime consumption in alcohol dependence from grey-matter pattern information.

Acta psychiatrica Scandinavica
OBJECTIVE: We investigated the potential of computer-based models to decode diagnosis and lifetime consumption in alcohol dependence (AD) from grey-matter pattern information. As machine-learning approaches to psychiatric neuroimaging have recently c...

Depression and alcohol use disorder at antiretroviral therapy initiation led to disengagement from care in South Africa.

PloS one
We sought to assess mental health at the time of antiretroviral therapy (ART) initiation and subsequent retention in care over a six-month follow-up period. A total of 136 people living with HIV in South Africa were administered surveys measuring dem...

Counting the cold ones: A comparison of methods measuring total alcohol consumption of managed alcohol program participants.

Drug and alcohol review
INTRODUCTION AND AIMS: Managed alcohol programs (MAP) aim to reduce harms experienced by unstably housed individuals with alcohol use disorders by providing regulated access to beverage alcohol, usually alongside housing, meals and other supports. Th...

Mobile phone sensors and supervised machine learning to identify alcohol use events in young adults: Implications for just-in-time adaptive interventions.

Addictive behaviors
BACKGROUND: Real-time detection of drinking could improve timely delivery of interventions aimed at reducing alcohol consumption and alcohol-related injury, but existing detection methods are burdensome or impractical.

An EEG-based functional connectivity measure for automatic detection of alcohol use disorder.

Artificial intelligence in medicine
BACKGROUND: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and m...

Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling.

Journal of medical systems
Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 imag...

Canonical variate regression.

Biostatistics (Oxford, England)
In many fields, multi-view datasets, measuring multiple distinct but interrelated sets of characteristics on the same set of subjects, together with data on certain outcomes or phenotypes, are routinely collected. The objective in such a problem is o...

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...

Support vector machine and fuzzy C-mean clustering-based comparative evaluation of changes in motor cortex electroencephalogram under chronic alcoholism.

Medical & biological engineering & computing
In this study, the magnitude and spatial distribution of frequency spectrum in the resting electroencephalogram (EEG) were examined to address the problem of detecting alcoholism in the cerebral motor cortex. The EEG signals were recorded from chroni...

Augmenting Common Spatial Patterns to deep learning networks for improved alcoholism detection using EEG signals.

Computers in biology and medicine
One of the main risk factors for numerous health problems is excessive drinking. Alcoholism is a severe disorder that can affect a person's thinking and cognitive abilities. Early detection of alcoholism can help the subject regain control over their...