A new electron monitor unit (MU) calculator program called "eMUc" was developed to provide a convenient electron MU calculation platform for the physics and radiotherapy staff in electron radiotherapy. The program was written using the Microsoft Visual Basic.net framework and has a user-friendly front-end window with the following features: (1) Apart from using the well-known polynomial curvefitting method for the interpolation and extrapolation of relative output factors (ROFs), an exponential curve-fitting method was used to obtain better results. (2) A new algorithm was used to acquire the radius in each angular segment in the irregular electron field during the sector integration. (3) A comprehensive graphical user interface running on the Microsoft Windows operating system was used. (4) Importing irregular electron cutout field images to the calculator program was simplified by using only a commercial optical scanner. (5) Interlocks were provided when the input patient treatment parameters could not be handled by the calculator database accurately. (6) A patient treatment record could be printed out as an electronic file or hard copy and transferred to the patient database. The data acquisition mainly required ROF measurements using various circular cutouts for all the available electron energies and applicators for our Varian 21 EX linear accelerator. To verify and implement the calculator, the measured results using our specific designed irregular and clinical cutouts were compared to those predicted by the calculator. Both agreed well with an error of +/-2%.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722481 | PMC |
http://dx.doi.org/10.1120/jacmp.v7i1.2183 | DOI Listing |
JMIR Form Res
December 2024
Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, United States.
Background: Anxiety disorders are common in alcohol use disorder (AUD) treatment patients. Such co-occurring conditions ("comorbidity") have negative prognostic implications for AUD treatment outcomes, yet they commonly go unaddressed in standard AUD care. Over a decade ago, we developed and validated a cognitive behavioral therapy intervention to supplement standard AUD care that, when delivered by trained therapists, improves outcomes in comorbid patients.
View Article and Find Full Text PDFChemosphere
December 2024
Department of Civil, Environmental and Ocean Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, NJ, 07030, USA. Electronic address:
Phosphate (PO(III)) contamination in water bodies poses significant environmental challenges, necessitating efficient and accurate methods to predict and optimize its removal. The current study addresses this issue by predicting the adsorption capacity of PO(III) ions onto biochar-based materials using five probabilistic machine learning models: eXtreme Gradient Boosting LSS (XGBoostLSS), Natural Gradient Boosting, Bayesian Neural Networks (NN), Probabilistic NN, and Monte-Carlo Dropout NN. Utilizing a dataset of 2952 data points with 16 inputs, XGBoostLSS demonstrated the highest R (0.
View Article and Find Full Text PDFJ Neurol Sci
December 2024
Computational and Translational Neuroscience Laboratory, Institute of Cognitive Sciences and Technologies, National Research Council (CTNLab-ISTC-CNR), Via Gian Domenico Romagnosi 18A, Rome 00196, Italy; AI2Life s.r.l., Innovative Start-Up, ISTC-CNR Spin-Off, Via Sebino 32, Rome 00199, Italy. Electronic address:
Alzheimer's disease (AD), the most common neurodegenerative disorder world-wide, presents sex-specific differences in its manifestation and progression, necessitating personalized diagnostic approaches. Current procedures are often costly and invasive, lacking consideration of sex-based differences. This study introduces an explainable machine learning (ML) system to predict and differentiate the progression of AD based on sex, using non-invasive, easily collectible predictors such as neuropsychological test scores and sociodemographic data, enabling its application in every day clinical settings.
View Article and Find Full Text PDFComput Methods Programs Biomed
December 2024
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy.
Background And Objective: Dysfunction of the right ventricular outflow tract (RVOT) is a common long-term complication following surgical repair in patients with congenital heart disease. Transcatheter pulmonary valve implantation (TPVI) offers a viable alternative to surgical pulmonary valve replacement (SPVR) for treating pulmonary regurgitation but not all RVOT anatomies are suitable for TPVI. To identify a suitable landing zone (LZ) for TPVI, three-dimensional multiphase (4D) computed tomography (CT) is used to evaluate the size, shape, and dynamic behavior of the RVOT throughout the cardiac cycle.
View Article and Find Full Text PDFHealthc Technol Lett
December 2024
ITI/LARSyS, Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal.
A thorough understanding of surgical anatomy is essential for preparing and training medical students to become competent and skilled surgeons. While Virtual Reality (VR) has shown to be a suitable interaction paradigm for surgical training, traditional anatomical VR models often rely on simple labels and arrows pointing to relevant landmarks. Yet, studies have indicated that such visual settings could benefit from knowledge maps as such representations explicitly illustrate the conceptual connections between anatomical landmarks.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!