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Machine-learning based quantification of lung shunt fraction from 99mTc-MAA SPECT/CT for selective internal radiation therapy of liver tumors using TriDFusion (3DF).
EJNMMI Phys
March 2025
Departments of Medical Physics, Memorial Sloan Kettering Cancer Center, 1250 First Avenue, New York, NY, 10065, USA.
Background: Prior to selective internal radiotherapy of liver tumors, a determination of the lung shunt fraction (LSF) is performed using 99mTc- macroaggregated albumin (99mTc-MAA) injected into the hepatic artery. Most commonly planar but sometimes SPECT/CT images are acquired upon which regions of interests are drawn manually to define the liver and the lung. The LSF is then calculated by taking the count ratios between these two organs.
View Article and Find Full Text PDFMedical Misinformation in AI-Assisted Self-Diagnosis: Development of a Method (EvalPrompt) for Analyzing Large Language Models.
JMIR Form Res
March 2025
Department of Management Sciences and Engineering, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada, 1 5198884567 ext 33279.
Background: Rapid integration of large language models (LLMs) in health care is sparking global discussion about their potential to revolutionize health care quality and accessibility. At a time when improving health care quality and access remains a critical concern for countries worldwide, the ability of these models to pass medical examinations is often cited as a reason to use them for medical training and diagnosis. However, the impact of their inevitable use as a self-diagnostic tool and their role in spreading health care misinformation has not been evaluated.
View Article and Find Full Text PDFUnderstanding the Capacitive and Diffusion-Controlled Behavior of Electrophoretically Deposited VCT on Carbon Yarn as a Potential Anode for Asymmetric Devices.
ACS Omega
March 2025
CENIMAT|I3N, Materials Science Department, NOVA School of Science and Technology, (NOVA FCT) University of Lisbon, 2829-516 Caparica, Portugal.
Recently, a novel class of emerging 2D materials identified as MXene have been revolutionizing the fabrication and development of flexible energy storage systems, i.e., batteries and supercapacitors.
View Article and Find Full Text PDFArtificial intelligence in healthcare education: evaluating the accuracy of ChatGPT, Copilot, and Google Gemini in cardiovascular pharmacology.
Front Med (Lausanne)
February 2025
Division of Pulmonary, Critical Care, and Sleep Medicine, School of Medicine, Case Western Reserve University, Cleveland, OH, United States.
Background: Artificial intelligence (AI) is revolutionizing medical education; however, its limitations remain underexplored. This study evaluated the accuracy of three generative AI tools-ChatGPT-4, Copilot, and Google Gemini-in answering multiple-choice questions (MCQ) and short-answer questions (SAQ) related to cardiovascular pharmacology, a key subject in healthcare education.
Methods: Using free versions of each AI tool, we administered 45 MCQs and 30 SAQs across three difficulty levels: easy, intermediate, and advanced.
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