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ARDD 2020: from aging mechanisms to interventions.

Aging
Aging is emerging as a druggable target with growing interest from academia, industry and investors. New technologies such as artificial intelligence and advanced screening techniques, as well as a strong influence from the industry sector may lead t...

The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics.

International journal of environmental research and public health
This study investigated the diagnostic accuracy of using an artificial neural network (ANN) for the prediction of metabolic syndrome (MetS) based on socioeconomic status and lifestyle factors. The data of 27,415 subjects who went through examinations...

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...

Multifactorial 10-Year Prior Diagnosis Prediction Model of Dementia.

International journal of environmental research and public health
Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the ...

Natural language processing of lifestyle modification documentation.

Health informatics journal
Lifestyle modification, including diet, exercise, and tobacco cessation, is the first-line treatment of many disorders including hypertension, obesity, and diabetes. Lifestyle modification data are not easily retrieved or used in research due to thei...

Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing.

International journal of medical informatics
INTRODUCTION: Previous biomedical studies identified many lifestyle exposures that could possibly represent risk factors for dementia in general or dementia due to Alzheimer's disease (AD). These lifestyle exposures are mainly mentioned in free-text ...

Application of Machine Learning to Identify Clustering of Cardiometabolic Risk Factors in U.S. Adults.

Diabetes technology & therapeutics
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...

Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test.

PloS one
Diabetes is a large healthcare burden worldwide. There is substantial evidence that lifestyle modifications and drug intervention can prevent diabetes, therefore, an early identification of high risk individuals is important to design targeted preven...