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Background: Dosimetric commissioning and quality assurance (QA) for linear accelerators (LINACs) present a significant challenge for clinical physicists due to the high measurement workload and stringent precision standards. This challenge is exacerbated for radiosurgery LINACs because of increased measurement uncertainty and more demanding setup accuracy for small-field beams. Optimizing physicists' effort during beam measurements while ensuring the quality of the measured data is crucial for clinical efficiency and patient safety.

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Pelvic sheet binders: Are doctors placing them in the correct position?

Afr J Emerg Med

December 2024

Division of Emergency Medicine, Faculty of Health Sciences, School of Clinical Medicine, University of the Witwatersrand, Johannesburg, South Africa.

Introduction: Unstable pelvic fractures cause significant bleeding, morbidity, and mortality. Commercially available Pelvic Circumferential Compression Devices (PCCDs) are used in the initial resuscitation and management of these cases. In the trauma-burdened, resource limited setting of Southern Africa, the available alternative is a pelvic sheet binder (PSB).

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The use of a ChatGPT-4-based chatbot in teledermatology: A retrospective exploratory study.

J Dtsch Dermatol Ges

January 2025

Sheba Medical Center, Tel Hashomer, Sackler School of Medicine, Faculty of Medical and Health Sciences, Tel Aviv University, Israel.

Background And Objectives: Integration of artificial intelligence in healthcare, particularly ChatGPT, is transforming medical diagnostics and may benefit teledermatology. This exploratory study compared image description and differential diagnosis generation by a ChatGPT-4 based chatbot with human teledermatologists.

Patients And Methods: This retrospective study compared 154 teledermatology consultations (December 2023-February 2024) with ChatGPT-4's performance in image descriptions and diagnoses.

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Context.—: All member boards of the American Board of Medical Specialties have continuing certification (ie, maintenance of certification) programs. The efficacy of these programs has been questioned and, therefore, warrants study.

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Accurately predicting carbon prices is crucial for effective government decision-making and maintenance the stable operation of carbon markets. However, the instability and nonlinearity of carbon prices, driven by the complex interaction between economic, environmental, and political factors, often result in inaccurate predictions. To confront this challenge, this paper proposed a carbon price prediction model that integrates dual decomposition integration and error correction.

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