Results 261 to 270 of about 1,167,178 (384)

Enhanced dose prediction for head and neck cancer artificial intelligence‐driven radiotherapy based on transfer learning with limited training data

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Training deep learning dose prediction models for the latest cutting‐edge radiotherapy techniques, such as AI‐based nodal radiotherapy (AINRT) and Daily Adaptive AI‐based nodal radiotherapy (DA‐AINRT), is challenging due to limited data.
Hui‐Ju Wang   +5 more
wiley   +1 more source

Tracking the Track: The Impact of Different Grazing Strategies on Managing Equine Obesity. [PDF]

open access: yesAnimals (Basel)
Cameron L   +5 more
europepmc   +1 more source

Assessing proton plans with three different beam delivery systems versus photon plans for head and neck tumors

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose To compare plan quality among photon volumetric modulated arc therapy (VMAT) and intensity‐modulated proton therapy (IMPT) with robustness using three different proton beam delivery systems with various spot size (σ) ranges: cyclotron‐generated proton beams (CPBs) (σ: 2.7–7.0 mm), linear accelerator proton beams (LPBs) (σ: 2.9–5.5 mm),
Tara Gray   +9 more
wiley   +1 more source

Left hippocampus sparing model for glioblastoma radiotherapy by utilizing knowledge‐based planning and multi‐criteria optimization

open access: yesJournal of Applied Clinical Medical Physics, EarlyView.
Abstract Purpose Results of a prospective, randomized controlled trial at our institute demonstrate an association between the dose to the left hippocampus and neurocognitive decline post‐radiotherapy for patients with glioblastoma. To minimize the dose to the left hippocampus, a left hippocampus sparing model was created using RapidPlan (RP) and multi‐
Shima Y. Tari   +9 more
wiley   +1 more source

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