Results 211 to 220 of about 478,616 (367)

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

open access: yesJournal 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   +4 more
wiley   +1 more source

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

open access: yesJournal 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   +5 more
wiley   +1 more source

Taste buds: cells, signals and synapses

open access: yesNature Reviews Neuroscience, 2017
S. Roper, Nirupa Chaudhari
semanticscholar   +1 more source

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

open access: yesJournal 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   +8 more
wiley   +1 more source

Practical challenges in data‐driven interpolation: Dealing with noise, enforcing stability, and computing realizations

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary In this contribution, we propose a detailed study of interpolation‐based data‐driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, that is, we analyze frequency‐response data.
Quirin Aumann, Ion Victor Gosea
wiley   +1 more source

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