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The journal of physical chemistry. A
Dec 13, 2022
The correct description of catalytic reactions happening on bimetallic particles is not feasible without proper accounting of the segregation process. In this study, we tried to shed light on the structure of large CoCu particles, for which quite con...
The journal of physical chemistry. A
Dec 1, 2022
Recently, the development of machine learning (ML) potentials has made it possible to perform large-scale and long-time molecular simulations with the accuracy of quantum mechanical (QM) models. However, for different levels of QM methods, such as de...
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Nov 28, 2022
This paper introduces a novel computational method to simulate and predict radiation dose profiles in a water phantom irradiated by X-rays of 6 and 15 MV at different depths and field sizes using Artificial Neural Networks within the error margin req...
Nature communications
Nov 24, 2022
Recurrent neural networks have seen widespread use in modeling dynamical systems in varied domains such as weather prediction, text prediction and several others. Often one wishes to supplement the experimentally observed dynamics with prior knowledg...
Magnetic resonance in medicine
Nov 11, 2022
PURPOSE: A supervised deep learning (DL) approach for frequency and phase correction (FPC) of MRS data recently showed encouraging results, but obtaining transients with labels for supervised learning is challenging. This work investigates the feasib...
Journal of chemical information and modeling
Nov 5, 2022
Designing highly selective molecules for a drug target protein is a challenging task in drug discovery. This task can be regarded as a multiobjective problem that simultaneously satisfies criteria for various objectives, such as selectivity for a tar...
Journal of chemical theory and computation
Nov 1, 2022
We present two machine learning methodologies that are capable of predicting diffusion Monte Carlo (DMC) energies with small data sets (≈60 DMC calculations in total). The first uses voxel deep neural networks (VDNNs) to predict DMC energy densities ...
Physics in medicine and biology
Oct 19, 2022
. Computed tomography (CT) to material property conversion dominates proton range uncertainty, impacting the quality of proton treatment planning. Physics-based and machine learning-based methods have been investigated to leverage dual-energy CT (DEC...
BMC medical informatics and decision making
Oct 17, 2022
Cross-validation (CV) is a resampling approach to evaluate machine learning models when sample size is limited. The number of all possible combinations of folds for the training data, known as CV rounds, are often very small in leave-one-out CV. Alte...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Oct 3, 2022
BACKGROUND PURPOSE: This study focused on developing a fast Monte Carlo (MC) plan verification platform via a deep learning (DL)-based denoising approach. It can maintain the MC dose calculation accuracy while significantly reducing the computation t...