In this study, postimplantation human epiblast and amnion development are modeled using a stem cell-based embryoid system. A dataset of 3697 fluorescent images, along with tissue, cavity, and cell masks, is generated from experimental data. A computa...
Rare diseases, such as Mucopolysaccharidosis (MPS), present significant challenges to the healthcare system. Some of the most critical challenges are the delay and the lack of accurate disease diagnosis. Early diagnosis of MPS is crucial, as it has t...
PURPOSE: To develop and validate a hybrid radiomics model to predict the overall survival in pancreatic cancer patients and identify risk factors that affect patient prognosis.
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...
Optimizing clinical pathways is pivotal for enhancing healthcare delivery, yet traditional methods are increasingly insufficient in the face of complex, personalized medical demands. This paper introduces an innovative optimization framework that fus...
The adoption of Artificial Intelligence (AI) is reshaping the labor market; however, individuals' perceptions of its impact remain inconsistent. This study investigates the presence of the Invulnerability Bias (IB), where workers perceive that AI wil...
Alzheimer's disease (AD) presents a pressing global health challenge, demanding improved strategies for early detection and understanding its progression. In this study, we address this need by employing survival analysis techniques to predict transi...
Deep learning for microbiome analysis has shown potential for understanding microbial communities and human phenotypes. Here, we propose an approach, Transformer-based Robust Principal Component Analysis(TRPCA), which leverages the strengths of trans...
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