Results 51 to 60 of about 433,523 (290)

BreastWatch: A Varian Eclipse script tool for Community‐Based automatic evaluation of breast treatment plans

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose This work introduces BreastWatch, a Varian Eclipse script tool designed to help medical physicists, dosimetrists, and radiation oncologists easily inspect and improve External Beam Breast Treatment (EBBT) plans using automatic evaluation of protocol dose‐constraints enhanced by a Community‐Based approach.
Stefano Agostinelli, Daniele Zefiro, Stefania Garelli, Francesca Cavagnetto, Marco Gusinu, Monica Bevegni, Gladys Blandino, Alessandra Fozza, Fabrizio Levrero   +8 more
wiley   +1 more source

The peculiar statistical mechanics of optimal learning machines [PDF]

Journal of Statistical Mechanics: Theory and Experiment, 2019
17 pages, 4 ...
openaire   +4 more sources

Open‐source deep‐learning models for segmentation of normal structures for prostatic and gynecological high‐dose‐rate brachytherapy: Comparison of architectures

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background The use of deep learning‐based auto‐contouring algorithms in various treatment planning services is increasingly common. There is a notable deficit of commercially or publicly available models trained on large or diverse datasets containing high‐dose‐rate (HDR) brachytherapy treatment scans, leading to poor performance on images ...
Andrew J. Krupien, Yasin Abdulkadir, Dishane C. Luximon, John Charters, Huiming Dong, Jonathan Pham, Dylan O'Connell, Jack Neylon, James M. Lamb   +8 more
wiley   +1 more source

Predicting COVID-19 statistics using machine learning regression model: Li-MuLi-Poly [PDF]

, 2021
Hari Singh, Seema Bawa
openalex   +1 more source

An extension to the OVH concept for knowledge‐based dose volume histogram prediction in lung tumor volumetric‐modulated arc therapy

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Volumetric‐modulated arc therapy (VMAT) treatment planning allows a compromise between a sufficient coverage of the planning target volume (PTV) and a simultaneous sparing of organs‐at‐risk (OARs). Particularly in the case of lung tumors, deciding whether it is possible or worth spending more time on further improvements of a treatment
Johann Brand, Juliane Szkitsak, Oliver J. Ott, Christoph Bert, Stefan Speer   +4 more
wiley   +1 more source

Predicting Cervical Cancer Outcomes: Statistics, Images, and Machine Learning [PDF]

, 2021
Wei Luo
openalex   +1 more source

Novel CT radiomics models for the postoperative prediction of early recurrence of resectable pancreatic adenocarcinoma: A single‐center retrospective study in China

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To assess the predictive capability of CT radiomics features for early recurrence (ER) of pancreatic ductal adenocarcinoma (PDAC). Methods Postoperative PDAC patients were retrospectively selected, all of whom had undergone preoperative CT imaging and surgery. Both patients with resectable or borderline‐resectable pancreatic cancer met
Xinze Du, Yongsu Ma, Kexin Wang, Xiejian Zhong, Jianxin Wang, Xiaodong Tian, Xiaoying Wang, Yinmo Yang   +7 more
wiley   +1 more source

A Python package for fast GPU‐based proton pencil beam dose calculation

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Open‐source GPU‐based Monte Carlo (MC) proton dose calculation algorithms provide high speed and unparalleled accuracy but can be complex to integrate with new applications and remain slower than GPU‐based pencil beam (PB) methods, which sacrifice some physical accuracy for sub‐second plan calculation.
Mahasweta Bhattacharya, Calin Reamy, Heng Li, Junghoon Lee, William T. Hrinivich   +4 more
wiley   +1 more source

Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case [PDF]

, 2021
Emma Viviani, Luca Di Persio, Matthias Ehrhardt   +2 more
openalex   +1 more source

Machine Learning: Deepest Learning as Statistical Data Assimilation Problems

Neural Computation, 2018
We formulate an equivalence between machine learning and the formulation of statistical data assimilation as used widely in physical and biological sciences. The correspondence is that layer number in a feedforward artificial network setting is the analog of time in the data assimilation setting.
Paul J. Rozdeba, Henry D. I. Abarbanel, Sasha Shirman   +2 more
openaire   +4 more sources