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...
International journal of environmental research and public health
Apr 10, 2019
A large number of people suffer from certain types of osteoarthritis, such as knee, hip, and spine osteoarthritis. A correct prediction of osteoarthritis is an essential step to effectively diagnose and prevent severe osteoarthritis. Osteoarthritis i...
In order to develop an equation that integrates multiple clinical factors including signs and symptoms associated with uraemia to assess the initiation of dialysis, we conducted a retrospective cohort study including 25 haemodialysis centres in Mainl...
Journal of infection and public health
Apr 10, 2019
BACKGROUND: Middle East Respiratory Syndrome (MERS) is a major infectious disease which has affected the Middle Eastern countries, especially the Kingdom of Saudi Arabia (KSA) since 2012. The high mortality rate associated with this disease has been ...
OBJECTIVE: Machine learning techniques have demonstrated superior discrimination compared to conventional statistical approaches in predicting trauma death. The objective of this study is to evaluate whether machine learning algorithms can be used to...
IEEE journal of biomedical and health informatics
Apr 9, 2019
Human activity recognition has been widely used in healthcare applications such as elderly monitoring, exercise supervision, and rehabilitation monitoring. Compared with other approaches, sensor-based wearable human activity recognition is less affec...
Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation
Apr 9, 2019
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.
AIM: Out-of-hospital cardiac arrest (OHCA) is a major healthcare burden, and prognosis is critical in decision-making for treatment and the withdrawal of life-sustaining therapy. This study aimed to develop and validate a deep-learning-based out-of-h...
BACKGROUND: New technologies to improve post-stroke rehabilitation outcomes are of great interest and have a positive impact on functional, motor, and cognitive recovery. Identifying the most effective rehabilitation intervention is a recognized prio...
OBJECTIVES: The purpose of this study was to compare the image quality of coronary computed tomography angiography (CTA) subjected to deep learning-based image restoration (DLR) method with images subjected to hybrid iterative reconstruction (IR).
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.