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...
IEEE/ACM transactions on computational biology and bioinformatics
Apr 9, 2019
Breast cancer is one of the most common cancers all over the world, which bring about more than 450,000 deaths each year. Although this malignancy has been extensively studied by a large number of researchers, its prognosis is still poor. Since thera...
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.
International journal of computer assisted radiology and surgery
Apr 9, 2019
PURPOSE: In recent years, with the increasing incidence of cervical cancer, it is a tedious and time-consuming task with unsatisfying accuracy to manually recognize the cells. Machine recognition can be a good solution, but it suffers from the diffic...
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...
Hierarchical processing is pervasive in the brain, but its computational significance for learning under uncertainty is disputed. On the one hand, hierarchical models provide an optimal framework and are becoming increasingly popular to study cogniti...
Cluster of microcalcifications can be an early sign of breast cancer. In this paper, we propose a novel approach based on convolutional neural networks for the detection and segmentation of microcalcification clusters. In this work, we used 283 mammo...
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).
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