PURPOSE: In order to minimize errors during achieving the targeted alignment of the total knee arthroplasty (TKA) components, robotic-assisted surgery has been introduced with the aim to help surgeons to improve implant survival, clinical outcomes, a...
PURPOSE: To compare performance of 1-mm deep learning reconstruction (DLR) with 3-mm routine MRI imaging for the delineation of pituitary axis and identification of cavernous sinus invasion for pituitary macroadenoma.
Personalized medicine refers to the tailoring of diagnostics and therapeutics to individuals based on one's biological, social, and behavioral characteristics. While personalized dental medicine is still far from being a reality, advanced artificial ...
Healthcare has well-known challenges with safety, quality, and effectiveness, and many see artificial intelligence (AI) as essential to any solution. Emerging applications include the automated synthesis of best-practice research evidence including s...
Today, society is more aware of their well-being and health, making wearable devices a new and affordable way to track them continuously. Smartwatches allow access to daily vital physiological measurements, which help people to be aware of their heal...
BACKGROUND: Artificial intelligence (AI) and machine learning are transforming the optimization of clinical and patient workflows in healthcare. There is a need for research to specify clinical requirements for AI-enhanced care pathway planning and s...
BACKGROUND: Cis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the spatio-temporal pattern of transcription; they are involved in a wide range of pivotal processes such as the development of specific cell-lines/tissues ...
Hand gesture recognition is one of the most widely explored areas under the human-computer interaction domain. Although various modalities of hand gesture recognition have been explored in the last three decades, in recent years, due to the availabil...
Deep neural network (DNN) based methods have shown promising performances for low-dose computed tomography (LDCT) imaging. However, most of the DNN-based methods are trained on simulated labeled datasets, and the low-dose simulation algorithms are us...
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