Scandinavian journal of trauma, resuscitation and emergency medicine
Mar 4, 2020
BACKGROUND: In emergency medical services (EMSs), accurately predicting the severity of a patient's medical condition is important for the early identification of those who are vulnerable and at high-risk. In this study, we developed and validated an...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
The goal of this study was to investigate the application of machine learning models capable of capturing multiplica tive and temporal clinical risk factors for outcome prediction inpatients with aneurysmal subarachnoid hemorrhage (aSAH). We examined...
International journal of medical informatics
Mar 3, 2020
OBJECTIVE: Predicting the risk of falls in advance can benefit the quality of care and potentially reduce mortality and morbidity in the older population. The aim of this study was to construct and validate an electronic health record-based fall risk...
OBJECTIVE: To apply artificial intelligence (AI) for automated identification of corneal condition and prediction of the likelihood of need for future keratoplasty intervention from optical coherence tomography (OCT)-based corneal parameters.
OBJECTIVES: Amyotrophic lateral sclerosis (ALS) is a rare neurodegenerative disease that is characterised by the rapid degeneration of upper and lower motor neurons and has a fatal trajectory 3-4 years from symptom onset. Due to the nature of the con...
The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two w...
Over the past decade, there has been a groundswell of research interest in computer-based methods for objectively quantifying fibrotic lung disease on high resolution CT of the chest. In the past 5 years, the arrival of deep learning-based image anal...
BACKGROUND: Little is known about exercise cardiac power (ECP), defined as the ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise, on heart failure (HF) risk. We examined the association of ECP and the ...
Journal of pain and symptom management
Feb 21, 2020
CONTEXT: Prior work using symptom burden to predict emergency department (ED) visits among patients with cancer has used traditional statistical methods such as logistic regression (LR). Machine learning approaches for prediction, such as artificial ...
BACKGROUND AND OBJECTIVE: Published models predicting health related outcomes rely on clinical, claims and social determinants of health (SDH) data. Addressing the challenge of predicting with only SDH we developed a novel framework termed Stratified...
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