AIMC Topic: Risk Factors

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Moonstone: a novel natural language processing system for inferring social risk from clinical narratives.

Journal of biomedical semantics
BACKGROUND: Social risk factors are important dimensions of health and are linked to access to care, quality of life, health outcomes and life expectancy. However, in the Electronic Health Record, data related to many social risk factors are primaril...

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...

Identifying Factors That Affect Patient Survival After Orthotopic Liver Transplant Using Machine-Learning Techniques.

Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation
OBJECTIVES: Survival after liver transplant depends on pretransplant, peritransplant, and posttransplant factors. Identifying effective factors for patient survival after transplant can help transplant centers make better decisions.

A hybrid neural network model for predicting kidney disease in hypertension patients based on electronic health records.

BMC medical informatics and decision making
BACKGROUND: Disease prediction based on Electronic Health Records (EHR) has become one hot research topic in biomedical community. Existing work mainly focuses on the prediction of one target disease, and little work is proposed for multiple associat...

A Stroke Risk Detection: Improving Hybrid Feature Selection Method.

Journal of medical Internet research
BACKGROUND: Stroke is one of the most common diseases that cause mortality. Detecting the risk of stroke for individuals is critical yet challenging because of a large number of risk factors for stroke.

Deep learning for identifying environmental risk factors of acute respiratory diseases in Beijing, China: implications for population with different age and gender.

International journal of environmental health research
This study focuses on identifying environmental health risk factors related to acute respiratory diseases using deep learning method. Based on respiratory disease data, air pollution data and meteorological environmental data, cross-domain risk facto...

Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach.

BMC medical research methodology
BACKGROUND: Chronic respiratory symptoms involving bronchitis, cough and phlegm in children are underappreciated but pose a significant public health burden. Efforts for prevention and management could be supported by an understanding of the relative...

Feature-weighted survival learning machine for COPD failure prediction.

Artificial intelligence in medicine
Chronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting su...

Machine Learning for Prediction of Posttraumatic Stress and Resilience Following Trauma: An Overview of Basic Concepts and Recent Advances.

Journal of traumatic stress
Posttraumatic stress responses are characterized by a heterogeneity in clinical appearance and etiology. This heterogeneity impacts the field's ability to characterize, predict, and remediate maladaptive responses to trauma. Machine learning (ML) app...