Cardiovascular digital twins (CDTs) have the potential to transform precision medicine by enabling tailored insights, continuous monitoring, and personalized simulations of cardiovascular dynamics through virtual representations of the cardiovascular... read more
Uveal melanoma (UM) presents a formidable clinical challenge due to its marked resistance to radiotherapy. In this study, an integrative strategy combining machine learning models with high-throughput screening platforms was employed to identify nove... read more
Additive manufacturing (AM) is transforming industrial production; however, inevitable defects-such as spaghetti-like collapses, surface blemishes ("zits"), and stringing-substantially degrade product quality and mechanical performance. To overcome l... read more
Automating structural optimization of drug molecules for on-target potency by machine learning is an open challenge in chemistry. Here, we capitalize on the ability of chemical language models (CLMs) to learn from sequential data and design new molec... read more
The Wnt protein family plays a critical role in cell development, with each Wnt protein interacting differently with the Wntless (Wls) membrane protein through distinct binding residues. A direct comparison and elucidation of the molecular mechanisms... read more
Optical character recognition is a technology that turns texts and scanned documents into digital formats. The practical applications of OCR systems face a lot of challenges because of heterogeneity in scripts, font styles, and different quality imag... read more
Artificial intelligence (AI) language models are increasingly being explored as tools to support medical education and clinical care. Evaluating their performance on valid and reliable assessments such as board certification exams may provide insight... read more
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