AIMC Topic: Risk Factors

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Identifying the predictive effectiveness of a genetic risk score for incident hypertension using machine learning methods among populations in rural China.

Hypertension research : official journal of the Japanese Society of Hypertension
Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extensively in the medical field but rarely in the mining of genetic information. This study aims to deter...

A Deep Learning Approach to Predict Diabetes' Cardiovascular Complications From Administrative Claims.

IEEE journal of biomedical and health informatics
People with diabetes require lifelong access to healthcare services to delay the onset of complications. Their disease management processes generate great volumes of data across several domains, from clinical to administrative. Difficulties in access...

Sociodemographic risk factors of under-five stunting in Bangladesh: Assessing the role of interactions using a machine learning method.

PloS one
This paper aims to demonstrate the importance of studying interactions among various sociodemographic risk factors of childhood stunting in Bangladesh with the help of an interpretable machine learning method. Data used for the analyses are extracted...

Machine learning models of ischemia/hemorrhage in moyamoya disease and analysis of its risk factors.

Clinical neurology and neurosurgery
OBJECT: This study aimed to determine the risk factors of ischemic/hemorrhagic stroke in patients suffering moyamoya disease (MMD), as well as to compare the effects of six analysis methods.

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.

Frontiers of medicine
The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors includin...

Machine Learning to Predict Fascial Dehiscence after Exploratory Laparotomy Surgery.

The Journal of surgical research
BACKGROUND: Fascial dehiscence following exploratory laparotomy is associated with significant morbidity and increased mortality. Previously published risk prediction models for fascial dehiscence are dated and limit a surgeon's ability to perform re...

Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review.

PloS one
BACKGROUND: Chest pain is amongst the most common reason for presentation to the emergency department (ED). There are many causes of chest pain, and it is important for the emergency physician to quickly and accurately diagnose life threatening cause...

Prediction Algorithm of Young Students' Physical Health Risk Factors Based on Deep Learning.

Journal of healthcare engineering
Young people's physical and mental health is the foundation of society's overall development and the key to improving people's health quality. Middle school students' physical examinations and monitoring work are a surefire way to ensure their health...

Predicting Incident Heart Failure in Women With Machine Learning: The Women's Health Initiative Cohort.

The Canadian journal of cardiology
BACKGROUND: Heart failure (HF) is a leading cause of cardiac morbidity among women, whose risk factors differ from those in men. We used machine-learning approaches to develop risk- prediction models for incident HF in a cohort of postmenopausal wome...