OBJECTIVES: Systemic lupus erythematosus (SLE) is a heterogeneous disease characterized by disease flares which can require hospitalization. Our objective was to apply machine learning methods to predict hospitalizations for SLE from electronic healt...
Healthy sleep is essential for the rejuvenation of the body and helps in maintaining good health. Many people suffer from sleep disorders that are characterized by abnormal sleep patterns. Automated assessment of such disorders using biomedical signa...
Highly sensitive and multimodal sensors have recently emerged for a wide range of applications, including epidermal electronics, robotics, health-monitoring devices and human-machine interfaces. However, cross-sensitivity prevents accurate measuremen...
Medical & biological engineering & computing
Jul 14, 2022
Deep learning provides the healthcare industry with the ability to analyse data at exceptional speeds without compromising on accuracy. These techniques are applicable to healthcare domain for accurate and timely prediction. Convolutional neural netw...
Drug side effects are closely related to the success and failure of drug development. Here we present a novel machine learning method for side effect prediction. The proposed method treats side effect prediction as a multi-label learning problem and ...
European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
Jul 14, 2022
BACKGROUND: Magnetic resonance imaging (MRI) is used to detect degenerative changes of the lumbar spine. SpineNet (SN), a computer vision-based system, performs an automated analysis of degenerative features in MRI scans aiming to provide high accura...
OBJECTIVE: Artificial intelligence (AI) has begun to play a pivotal role in hepatic imaging. This systematic scoping review summarizes the latest progress of AI in evaluating hepatic diseases based on computed tomography (CT) and magnetic resonance (...
To quantitatively assess pathological gait, we developed a novel smartphone application for full-body human motion tracking in real time from markerless video-based images using a smartphone monocular camera and deep learning. As training data for de...
Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demonstrate that it can surpass human performance. This paper mainly applies Deep Q-Network (DQN), which combines reinforcement learning and deep learning ...
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