Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown si...
International journal of computer assisted radiology and surgery
Apr 20, 2022
PURPOSE: Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of lung images in time dimension to ...
Journal of the Association for Research in Otolaryngology : JARO
Apr 20, 2022
Use of artificial intelligence (AI) is a burgeoning field in otolaryngology and the communication sciences. A virtual symposium on the topic was convened from Duke University on October 26, 2020, and was attended by more than 170 participants worldwi...
Chest radiography is one of the most widely used diagnostic methods in hospitals, but it is difficult to read clearly because several human organ tissues and bones overlap. Therefore, various image processing and rib segmentation methods have been pr...
Personalized modeling has long been anticipated to approach precise noninvasive blood glucose measurements, but challenged by limited data for training personal model and its unavoidable outlier predictions. To overcome these long-standing problems, ...
Head kinematics information is important as it is used to measure brain injury risk. Currently, head kinematics are measured using wearable devices or instrumentation mounted on the head. This paper evaluates the deep learning approach in predicting ...
INTRODUCTION: Both the pharmacological characteristics of blonanserin and its related small sample size studies suggest that blonanserin could alleviate social and cognitive dysfunctions in patients with schizophrenia. However, no large sample size s...
BACKGROUND: The application of virtual reality (VR) and robotic devices in neuromotor rehabilitation has provided promising evidence in terms of efficacy, so far. Usability evaluations of these technologies have been conducted extensively, but no ove...
BACKGROUND: Deep learning (DL) is an advanced machine learning approach used in different areas such as image analysis, bioinformatics, and natural language processing. A convolutional neural network (CNN) is a representative DL model that is highly ...
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