PURPOSE: Automated facial recognition technology based on deep learning has achieved high accuracy in diagnosing various endocrine diseases and genetic syndromes. This study attempts to establish a facial diagnostic system for Turner syndrome (TS) ba...
Neural networks : the official journal of the International Neural Network Society
Nov 10, 2020
In this study, we present a neural network that consists of nodes with heterogeneous sensitivity. Each node in a network is assigned a variable that determines the sensitivity with which it learns to perform a given task. The network is trained via a...
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Neural networks : the official journal of the International Neural Network Society
Nov 10, 2020
Attribution editing has achieved remarkable progress in recent years owing to the encoder-decoder structure and generative adversarial network (GAN). However, it remains challenging to generate high-quality images with accurate attribute transformati...
BACKGROUND: Sepsis is a life-threatening condition that occurs due to the body's reaction to infections, and it is a leading cause of morbidity and mortality in hospitals. Early prediction of sepsis onset facilitates early interventions that promote ...
BACKGROUND: Diagnosis of rib fractures plays an important role in identifying trauma severity. However, quickly and precisely identifying the rib fractures in a large number of CT images with increasing number of patients is a tough task, which is al...
PURPOSE: When using convolutional neural networks (CNNs) for segmentation of organs and lesions in medical images, the conventional approach is to work with inputs and outputs either as single slice [two-dimensional (2D)] or whole volumes [three-dime...
The objective of this study was to investigate the accuracy of a Deep Neural Network (DNN) in recognizing activities typical for hospitalized patients. A data collection study was conducted with 20 healthy volunteers (10 males and 10 females, age = 4...
This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 im...
International journal of molecular sciences
Nov 10, 2020
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient and successful rational drug design. Therefore, many binding affinity prediction methods have been developed. In recent years, since deep learning tech...
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