Results 161 to 170 of about 1,612,060 (336)

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

JACMP 2005–2009

Journal of Applied Clinical Medical Physics, EarlyView.
Timothy D. Solberg
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

JACMP 2025–2029 and beyond

Journal of Applied Clinical Medical Physics, EarlyView.
Michael Mills
wiley   +1 more source

Risk analysis of the Unity 1.5T MR‐Linac adapt‐to‐shape workflow

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Background and Purpose The adapt‐to‐shape (ATS) workflow on the Unity MR‐Linac (Elekta AB, Stockholm, Sweden) allows for full replanning including recontouring and reoptimization5. Additional complexity to this workflow is added when the adaptation involves the use of MIM Maestro (MIM Software, Cleveland, OH) software in conjunction with ...
Jiayi Liang, Eric Aliotta, Neelam Tyagi, Paola Godoy Scripes, Nicolas Côté, Ergys Subashi, Qijie Huang, Lian Sun, Ching‐Yun Chan, Angela Ng, Theresa Wunner, Victoria Brennan, Kaveh Zakeri, James Mechalakos   +13 more
wiley   +1 more source

An ergonomics training program for student notebook computer users: Preliminary outcomes of a six-year cohort study [PDF]

, 2013
Karen Jacobs, Jennifer Kaldenberg, Jackie Markowitz, Ellen Wuest, Miranda Hellman, Amarachi Umez-Eronini, Michael Arsenault, Bryce Walker, Victoria Hall, Marina Ciccarelli, Richard Parsons, Alice Barr   +11 more
openalex   +1 more source

Professionalism skills education in medical physics residency: Current state and perceived importance

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose The purpose of this study was to collect data on current practices for teaching and assessing professionalism in CAMPEP‐accredited residency programs. Methods A survey of 21 questions was sent to 160 program directors (PDs) of CAMPEP‐accredited residency programs.
Anna Rodrigues, Leah Schubert, Laura Padilla, Kristi Hendrickson, Hania Al‐Hallaq, Irina Vergalasova   +5 more
wiley   +1 more source

Virtual Reality simulator for dental anesthesia training in the inferior alveolar nerve block

Journal of Applied Oral Science
Objectives This study shows the development and validation of a dental anesthesia-training simulator, specifically for the inferior alveolar nerve block (IANB).
Cléber Gimenez CORRÊA, Maria Aparecida de Andrade Moreira MACHADO, Edith RANZINI, Romero TORI, Fátima de Lourdes Santos NUNES   +4 more
doaj   +1 more source

Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments

Journal of Applied Clinical Medical Physics, EarlyView.
Abstract Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra‐hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter‐fraction variability, inconsistent patient adherence still results in OAR variability.
Conor Sinclair Smith, Isabelle Gagne, Karl Otto, Carter Kolbeck, Joshua Giambattista, Abraham Alexander, Sonja Murchison, Andrew Pritchard, Erika Chin   +8 more
wiley   +1 more source

Fine-Tuning Large Language Models with User-Level Differential Privacy [PDF]

arXiv
We investigate practical and scalable algorithms for training large language models (LLMs) with user-level differential privacy (DP) in order to provably safeguard all the examples contributed by each user. We study two variants of DP-SGD with: (1) example-level sampling (ELS) and per-example gradient clipping, and (2) user-level sampling (ULS) and per-
arxiv