BACKGROUND: Clinical named entity recognition is the basic task of mining electronic medical records text, which are with some challenges containing the language features of Chinese electronic medical records text with many compound entities, serious...
The recent medical applications of deep-learning (DL) algorithms have demonstrated their clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm achieves a performance equivalent to that achieved by physicians i...
Structural brain alterations have been repeatedly reported in schizophrenia; however, the pathophysiology of its alterations remains unclear. Multivariate pattern recognition analysis such as support vector machines can classify patients and healthy ...
Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the ro...
BACKGROUND: Existing methods to reconstruct vascular structures from a computerized tomography (CT) angiogram rely on contrast injection to enhance the radio-density within the vessel lumen. However, pathological changes in the vasculature may be pre...
AIM: To develop a fully automatic algorithm to segment retinal cavitations on optical coherence tomography (OCT) images of macular telangiectasia type 2 (MacTel2).
Journal of investigative surgery : the official journal of the Academy of Surgical Research
Nov 23, 2020
OBJECTIVES: The accuracy of robotic surgery has been recognized by many doctors, but traditional robotic surgery requires 4-5 puncture holes in the operating area. With the popularization and application of single port laparoscopic surgery, the aesth...
The American journal of the medical sciences
Nov 23, 2020
INTRODUCTION: Some studies indicate an association between coronary artery disease (CAD) and osteoporosis. This case-control study examined the association between body composition and bone mineral content (BMC) and density (BMD) among patients with ...
OBJECTIVES: To evaluate the prediction performance of deep convolutional neural network (DCNN) based on ultrasound (US) images for the assessment of breast cancer molecular subtypes.
PURPOSE: The purpose of this study is to demonstrate a method for specific absorption rate (SAR) reduction for 2D T -FLAIR MRI sequences at 7 T by predicting the required adiabatic radiofrequency (RF) pulse power and scaling the RF amplitude in a sli...
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