AIMC Topic: Alcohol Drinking

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Leading consumption patterns of psychoactive substances in Colombia: A deep neural network-based clustering-oriented embedding approach.

PloS one
The number of health-related incidents caused using illegal and legal psychoactive substances (PAS) has dramatically increased over two decades worldwide. In Colombia, the use of illicit substances has increased up to 10.3%, while the consumption alc...

Audio-based Deep Learning Algorithm to Identify Alcohol Inebriation (ADLAIA).

Alcohol (Fayetteville, N.Y.)
BACKGROUND: Acute alcohol intoxication impairs cognitive and psychomotor abilities leading to various public health hazards such as road traffic accidents and alcohol-related violence. Intoxicated individuals are usually identified by measuring their...

Deep Learning for Identification of Alcohol-Related Content on Social Media (Reddit and Twitter): Exploratory Analysis of Alcohol-Related Outcomes.

Journal of medical Internet research
BACKGROUND: Many social media studies have explored the ability of thematic structures, such as hashtags and subreddits, to identify information related to a wide variety of mental health disorders. However, studies and models trained on specific the...

A machine learning-based biological aging prediction and its associations with healthy lifestyles: the Dongfeng-Tongji cohort.

Annals of the New York Academy of Sciences
This study aims to establish a biological age (BA) predictor and to investigate the roles of lifestyles on biological aging. The 14,848 participants with the available information of multisystem measurements from the Dongfeng-Tongji cohort were used ...

Predicting changes in substance use following psychedelic experiences: natural language processing of psychedelic session narratives.

The American journal of drug and alcohol abuse
: 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...

Host variables confound gut microbiota studies of human disease.

Nature
Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify causal relationships between host-associated microorganisms and pathology. The risk of obtaining false...

Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research
BACKGROUND: An estimated 425 million people globally have diabetes, accounting for 12% of the world's health expenditures, and the number continues to grow, placing a huge burden on the healthcare system, especially in those remote, underserved areas...

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

Drug and alcohol dependence
BACKGROUND: Transdermal biosensors offer a noninvasive, low-cost technology for the assessment of alcohol consumption with broad potential applications in addiction science. Older-generation transdermal devices feature bulky designs and sparse sampli...

How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

Drug and alcohol dependence
BACKGROUND: Evidence demonstrates that seeing alcoholic beverages in electronic media increases alcohol initiation and frequent and excessive drinking, particularly among young people. To efficiently assess this exposure, the aim was to develop the A...