Food research international (Ottawa, Ont.)
40086950
This work explored the light propagation of purees from a large variability of apple cultivar, storage period and heating duration based on their optical absorption (μ) and reduced scattering (μ') properties at 900-1650 nm, in order to better monitor...
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
40184907
Artificial intelligence (AI) has gained significant attention in various scientific fields due to its ability to process large datasets. In nuclear radiation physics, while AI presents exciting opportunities, it cannot replace physics-based models es...
A framework for parameter estimation and uncertainty quantification is crucial for understanding the mechanisms of biological interactions within complex systems and exploring their dynamic behaviors beyond what can be experimentally observed. Despit...
Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targeting capabilities, and multifunctional imaging modalities. Recent advancements in material engineering have enabled the development of nanoparticles ...
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
40112700
PURPOSE: This study aims to investigate estimation of patient-specific organ doses from CT scans via radiomics feature-based SVR models with training parameter optimization, and maximize SVR models' predictive accuracy and robustness via fine-tuning ...
SIGNIFICANCE: Investigating optical properties (OPs) is crucial in the field of biophotonics, as it has a broad impact on understanding light-tissue interactions. However, current techniques, such as inverse Monte Carlo simulations (IMCS), have limit...
This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict electronic portal imaging device (EPID) images based on MC-generated exit phase space energy fluence ...
. The dose distribution of lung cancer patients treated with the CyberKnife (CK) system is influenced by various factors, including tumor location and the direction of CK beams. The objective of this study is to present a deep learning approach that ...
BACKGROUND: Supervised machine learning is increasingly being used to estimate clinical predictive models. Several supervised machine learning models involve hyper-parameters, whose values must be judiciously specified to ensure adequate predictive p...
Journal of radiological protection : official journal of the Society for Radiological Protection
40334671
In this research work, we present our open-source Geant4-based Monte-Carlo simulation application, called RadField3D, for generating three-dimensional radiation field datasets for dosimetry. Accompanying, we introduce a fast, machine-interpretable da...