Accurate segmentation of brain tumors from magnetic resonance (MR) images play a pivot role in assisting diagnoses, treatments and postoperative evaluations. However, due to its structural complexities, e.g., fuzzy tumor boundaries with irregular sha...
By localizing microbubbles (MBs) in the vasculature, ultrasound localization microscopy (ULM) has recently been proposed, which greatly improves the spatial resolution of ultrasound (US) imaging and will be helpful for clinical diagnosis. Nevertheles...
The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has re...
In this paper, methods for scientifically inferring the causes of the falls-from-height accidents, that is, the initial fall postures, and reconstructing the fall accident are presented. For this purpose, the general types of fall were subdivided int...
In this paper, we applied a novel method for the detection of Alzheimer's disease (AD) based on a structural magnetic resonance imaging (sMRI) dataset. Specifically, the method involved a new classification algorithm of machine learning, named Genera...
Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recordi...
PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) vs glaucomatous optic neuropathy (GON) on color fundus photographs by the use of image recognition.
Artificial intelligence (AI) for the purpose of this review is an umbrella term for technologies emulating a nephropathologist's ability to extract information on diagnosis, prognosis, and therapy responsiveness from native or transplant kidney biops...
Neural networks : the official journal of the International Neural Network Society
Apr 1, 2020
Convolutional neural networks (CNNs), a popular type of deep neural network, have been actively applied to image recognition, object detection, object localization, semantic segmentation, and object instance segmentation. Accordingly, the applicabili...
Epoxidation is one of the reactions in drug metabolism. Since epoxide metabolites would bind with proteins or DNA covalently, drugs should avoid epoxidation metabolism in the body. Due to the instability of epoxide, it is difficult to determine epoxi...
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