AIMC Topic: Life Style
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A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data.
PloS one
Aug 19, 2021
Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity and mortality in COPD patients. Apart from patients with obvious EI, the identification of a such behavior during a real-life consultation is unreliable...
Using Wearables and Machine Learning to Enable Personalized Lifestyle Recommendations to Improve Blood Pressure.
IEEE journal of translational engineering in health and medicine
Jul 19, 2021
Blood pressure (BP) is an essential indicator for human health and is known to be greatly influenced by lifestyle factors, like activity and sleep factors. However, the degree of impact of each lifestyle factor on BP is unknown and may vary between ...
Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes.
Circulation research
Jun 10, 2021
Peripheral artery disease is an atherosclerotic disorder which, when present, portends poor patient outcomes. Low diagnosis rates perpetuate poor management, leading to limb loss and excess rates of cardiovascular morbidity and death. Machine learnin...
Prognosis
Risk Assessment
Life Style
Humans
Treatment Outcome
Aortic Aneurysm
Artificial Intelligence
Peripheral Arterial Disease
Behavior Therapy
Natural Language Processing
Machine Learning
Carotid Artery Diseases
Algorithms
Atherosclerosis
Forecasting
Supervised Machine Learning
Phenotype
Image Interpretation, Computer-Assisted
Improving brain age estimates with deep learning leads to identification of novel genetic factors associated with brain aging.
Neurobiology of aging
Apr 20, 2021
To study genetic factors associated with brain aging, we first need to quantify brain aging. Statistical models have been created for estimating the apparent age of the brain, or predicted brain age (PBA), using imaging data. Recent studies have refi...
Geographically weighted machine learning model for untangling spatial heterogeneity of type 2 diabetes mellitus (T2D) prevalence in the USA.
Scientific reports
Mar 26, 2021
Type 2 diabetes mellitus (T2D) prevalence in the United States varies substantially across spatial and temporal scales, attributable to variations of socioeconomic and lifestyle risk factors. Understanding these variations in risk factors contributio...
Ranking of a wide multidomain set of predictor variables of children obesity by machine learning variable importance techniques.
Scientific reports
Jan 21, 2021
The increased prevalence of childhood obesity is expected to translate in the near future into a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex, multifactorial etiology, that includes multiple and multidomain potenti...
Deep learning identifies partially overlapping subnetworks in the human social brain.
Communications biology
Jan 14, 2021
Complex social interplay is a defining property of the human species. In social neuroscience, many experiments have sought to first define and then locate 'perspective taking', 'empathy', and other psychological concepts to specific brain circuits. S...
ARDD 2020: from aging mechanisms to interventions.
Aging
Dec 30, 2020
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
Dec 11, 2020
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...
PCLiON: An Ontology for Data Standardization and Sharing of Prostate Cancer Associated Lifestyles.
International journal of medical informatics
Nov 7, 2020
BACKGROUND: Researches on Lifestyle medicine (LM) have emerged in recent years to garner wide attention. Prostate cancer (PCa) could be prevented and treated by positive lifestyles, but the association between lifestyles and PCa is always personalize...
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