BACKGROUND: To evaluate the precision of automated segmentation facilitated by deep learning (DL) and dose calculation in adaptive radiotherapy (ART) for nasopharyngeal cancer (NPC), leveraging synthetic CT (sCT) images derived from cone-beam CT (CBC...
BACKGROUND: Intra-aortic balloon pump (IABP) implantation in the perioperative period of cardiac surgery is an auxiliary treatment for cardiogenic shock. However, there is a lack of effective prediction models for preoperative IABP implantation.
Heydari et al. present an intriguing study examining the role of three long non-coding RNAs (lncRNAs)-H19, taurine upregulated gene 1 (TUG1), and colorectal neoplasia differentially expressed (CRNDE)-in the context of Coronavirus Disease 2019 (COVID-...
BACKGROUND: Suicide represents a significant challenge to public health that calls for a suitable intervention from the healthcare sector. Despite the typically low suicide rate among most Muslim nations, research indicates that there is an increase ...
BACKGROUND: The Anemia Control Model (ACM) is a decision support system powered by an artificial intelligence core designed to assist nephrologists in managing anemia therapy for in-center hemodialysis (HD) patients. This study aims to evaluate the c...
Extracting time-varying latent variables from computational cognitive models plays a key role in uncovering the dynamic cognitive processes that drive behaviors. However, existing methods are limited to inferring latent variable sequences in a relati...
This paper presents a novel system for optimizing Tai Chi movement training using computer vision and deep learning technologies. We developed a comprehensive framework incorporating multi-view pose estimation, temporal feature extraction, and real-t...
Digital twin (DT) technology is revolutionizing healthcare systems by leveraging real-time data integration and advanced analytics to enhance patient care, optimize clinical operations, and facilitate simulation. This study aimed to identify key rese...
It is well known that machine learning models require a high amount of annotated data to obtain optimal performance. Labelling Computed Tomography (CT) data can be a particularly challenging task due to its volumetric nature and often missing and/or ...
Telementoring in surgical training enables expert surgeons to provide real-time remote guidance to trainees. This technique is increasingly adopted to address surgical training gaps in low- and middle-income countries (LMICs), i.e., nations with a gr...
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