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| http://dx.doi.org/10.1001/jamanetworkopen.2024.32460 | DOI Listing |
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A prospective study comparing highly qualified Molecular Tumor Boards with AI-powered software as a medical device.
Int J Clin Oncol
December 2024
Translational Research Support Office, Division of Drug and Diagnostic Development Promotion, Department for the Promotion of Drug and Diagnostic Development, National Cancer Center Hospital East, 6-5-1 Kashiwanoha, Kashiwa, Chiba, 277-8577, Japan.
Background: The implementation of cancer precision medicine in Japan is deeply intertwined with insurance reimbursement policies and requires case-by-case reviews by Molecular Tumor Boards (MTBs), which impose considerable operational burdens on healthcare facilities. The extensive preparation and review times required by MTBs hinder their ability to efficiently assess comprehensive genomic profiling (CGP) test results. Despite attempts to optimize MTB operations, significant challenges remain.
View Article and Find Full Text PDFFirst comparison between artificial intelligence-guided coronary computed tomography angiography versus single-photon emission computed tomography testing for ischemia in clinical practice.
Coron Artery Dis
December 2024
Department of Cardiology, David Geffen School of Medicine, University of California, Los Angeles.
Background: Noninvasive cardiac testing with coronary computed tomography angiography (CCTA) and single-photon emission computed tomography (SPECT) are becoming alternatives to invasive angiography for the evaluation of obstructive coronary artery disease. We aimed to evaluate whether a novel artificial intelligence (AI)-assisted CCTA program is comparable to SPECT imaging for ischemic testing.
Methods: CCTA images were analyzed using an artificial intelligence convolutional neural network machine-learning-based model, atherosclerosis imaging-quantitative computed tomography (AI-QCT)ISCHEMIA.
AI-empowered applications effects on EFL learners' engagement in the classroom and academic procrastination.
BMC Psychol
December 2024
International Education Institute, University of St Andrews, St Andrews, KY16 9AJ, UK.
Background: In today's rapidly evolving educational landscape, AI-powered applications like ChatGPT, POE, and Duolingo are revolutionizing language education, offering personalized learning experiences in EFL. However, challenges such as student engagement and academic procrastination persist. This study delves into how these AI tools impact EFL learners' engagement and procrastination tendencies, aiming to inform effective technology integration in language instruction.
View Article and Find Full Text PDFDescriptive overview of AI applications in x-ray imaging and radiotherapy.
J Radiol Prot
December 2024
University Hospital of Heraklion, Crete, GREECE.
Artificial intelligence (AI) is transforming medical radiation applications by handling complex data, learning patterns, and making accurate predictions, leading to improved patient outcomes. This article examines the use of AI in optimizing radiation doses for X-ray imaging, improving radiotherapy outcomes, and briefly addresses the benefits, challenges, and limitations of AI integration into clinical workflows. In diagnostic radiology, AI plays a pivotal role in optimizing radiation exposure, reducing noise, enhancing image contrast, and lowering radiation doses, especially in high-dose procedures like computed tomography.
View Article and Find Full Text PDFEnhancing artificial intelligence-driven sleep apnea diagnosis: The critical importance of input signal proficiency with a focus on mandibular jaw movements.
J Prosthodont
December 2024
HP2 Laboratory, Inserm U1300, Grenoble Alpes University, Grenoble, France.
Purpose: This review aims to highlight the pivotal role of the mandibular jaw movement (MJM) signal in advancing artificial intelligence (AI)-powered technologies for diagnosing obstructive sleep apnea (OSA).
Methods: A scoping review was conducted to evaluate various aspects of the MJM signal and their contribution to improving signal proficiency for users.
Results: The comprehensive literature analysis is structured into four key sections, each addressing factors essential to signal proficiency.
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