AIMC Topic: Alcohol Drinking

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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 Sep 15, 2021
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...
United States Ethanol Social Media Natural Language Processing Alcohol Drinking Humans Deep Learning Adolescent
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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 Sep 3, 2021
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 ...
Machine Learning Forecasting Prospective Studies Female Aged Aged, 80 and over Cohort Studies Humans Follow-Up Studies Principal Component Analysis Smoking Alcohol Drinking Healthy Lifestyle Adult Male Aging Middle Aged Exercise China
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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...
Male Surveys and Questionnaires Emotions Natural Language Processing Substance-Related Disorders Hallucinogens Humans Alcohol Drinking Female Lysergic Acid Diethylamide Adult Psilocybin
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Host variables confound gut microbiota studies of human disease.

Nature Nov 4, 2020
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...
Humans Machine Learning Data Analysis Female Aged Case-Control Studies Feces ROC Curve Diabetes Mellitus, Type 2 Body Mass Index Gastrointestinal Microbiome Aged, 80 and over Young Adult Adult Male Middle Aged Diet Disease Life Style Confounding Factors, Epidemiologic RNA, Ribosomal, 16S Residence Characteristics Area Under Curve Gastrointestinal Motility Alcohol Drinking
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Identification of Potential Type II Diabetes in a Large-Scale Chinese Population Using a Systematic Machine Learning Framework.

Journal of diabetes research Sep 24, 2020
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...
Male Smoking Middle Aged Odds Ratio China Alcohol Drinking Surveys and Questionnaires Decision Making Medically Underserved Area Machine Learning Diabetes Mellitus, Type 2 Regression Analysis Humans Algorithms Logistic Models Decision Trees Area Under Curve Female Asian People Risk Factors Waist Circumference Aged Adult
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Using machine learning for real-time BAC estimation from a new-generation transdermal biosensor in the laboratory.

Drug and alcohol dependence Aug 1, 2020
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...
Breath Tests Smartphone Biosensing Techniques Family Characteristics Ethanol Laboratories Alcohol Drinking Humans Machine Learning Female Adult Male
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How much are we exposed to alcohol in electronic media? Development of the Alcoholic Beverage Identification Deep Learning Algorithm (ABIDLA).

Drug and alcohol dependence Jan 9, 2020
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...
Adolescent Wine Pattern Recognition, Automated Alcohol Drinking Alcoholic Beverages Algorithms Mass Media Female Beer Reproducibility of Results Humans Adult Male Deep Learning
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Recurrent Neural Networks for Early Detection of Heart Failure From Longitudinal Electronic Health Record Data: Implications for Temporal Modeling With Respect to Time Before Diagnosis, Data Density, Data Quantity, and Data Type.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods.
Electronic Health Records Female Reproducibility of Results Risk Factors Male Diagnosis, Computer-Assisted Incidence Time Factors Primary Health Care Longitudinal Studies Predictive Value of Tests Heart Failure Early Diagnosis Humans Smoking Neural Networks, Computer Alcohol Drinking Machine Learning California Vital Signs
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An Individualized Prediction Model for Long-term Lung Function Trajectory and Risk of COPD in the General Population.

Chest Sep 19, 2019
BACKGROUND: Prediction of future lung function will enable the identification of individuals at high risk of developing COPD, but the trajectory of lung function decline varies greatly among individuals. This study involved the development and valida...
Vital Capacity Bronchodilator Agents Serum Globulins Pulmonary Disease, Chronic Obstructive Alcohol Drinking Cohort Studies Cigarette Smoking Male Spirometry Electrocardiography Aging Alkaline Phosphatase Humans Triglycerides Longitudinal Studies Middle Aged Hematocrit Serum Albumin Age Factors Risk Assessment Machine Learning Dyspnea Leukocyte Count Cough Algorithms Lung Sex Factors Female Forced Expiratory Volume Body Height Adult
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Application of Machine Learning to Identify Clustering of Cardiometabolic Risk Factors in U.S. Adults.

Diabetes technology & therapeutics Apr 10, 2019
The aim of this study is to compare some machine learning methods with traditional statistical parametric analyses using logistic regression to investigate the relationship of risk factors for diabetes and cardiovascular (cardiometabolic risk) for U...
Middle Aged Aged Lipids Humans Risk Assessment Waist Circumference Aged, 80 and over Machine Learning Adolescent Metabolic Diseases Young Adult Algorithms United States Smoking Adult Female Body Mass Index Alcohol Drinking Male Risk Factors Cluster Analysis Life Style Cardiovascular Diseases
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