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Passing the learning curve in robotic mitral valve repair-what do we know in 2025?
Eur J Cardiothorac Surg
January 2025
Department of Cardiothoracic Surgery, University of Pittsburgh School of Medicine and UPMC Heart and Vascular Institute Pittsburgh, PA, USA.
Machine-Learning Modeling of Elemental Ferroelectric Bismuth Monolayer.
Phys Rev Lett
December 2024
Xi'an Jiaotong University, School of Microelectronics & State Key Laboratory for Mechanical Behavior of Materials, Xi'an 710049, China.
The bismuth monolayer has recently been experimentally identified as a novel platform for the investigation of two-dimensional single-element ferroelectric system. Here, we model the potential energy surface of a bismuth monolayer by employing a message-passing neural network and achieve an error smaller than 1.2 meV per atom.
View Article and Find Full Text PDFFrom preparation to success: assessing the effectiveness of Saudi Pharmacists Licensure Examination (SPLE) preparation strategies in Saudi Arabia.
Ir J Med Sci
January 2025
Department of Clinical Pharmacy, College of Pharmacy, King Khalid University, Abha, Saudi Arabia.
Aim: This study aimed to identify the most commonly used tools by recent pharmacy graduates who successfully passed the Saudi Pharmacists Licensure Examination (SPLE). It also sought to evaluate which tools were perceived as the most useful and representative of the exam content, while considering their monetary value and offering recommendations for future candidates.
Methods: A cross-sectional design was used, involving licensed pharmacists who graduated in 2019 or later and had successfully passed the SPLE.
The design space of E(3)-equivariant atom-centred interatomic potentials.
Nat Mach Intell
January 2025
Engineering Laboratory, University of Cambridge, Cambridge, UK.
Molecular dynamics simulation is an important tool in computational materials science and chemistry, and in the past decade it has been revolutionized by machine learning. This rapid progress in machine learning interatomic potentials has produced a number of new architectures in just the past few years. Particularly notable among these are the atomic cluster expansion, which unified many of the earlier ideas around atom-density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message-passing neural network with equivariant features that exhibited state-of-the-art accuracy at the time.
View Article and Find Full Text PDFDeep learning-based Monte Carlo dose prediction for heavy-ion online adaptive radiotherapy and fast quality assurance: A feasibility study.
Med Phys
January 2025
Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou, China.
Background: Online adaptive radiotherapy (OART) and rapid quality assurance (QA) are essential for effective heavy ion therapy (HIT). However, there is a shortage of deep learning (DL) models and workflows for predicting Monte Carlo (MC) doses in such treatments.
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