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Mass Casualty Incident Training in Immersive Virtual Reality: Quasi-Experimental Evaluation of Multimethod Performance Indicators.
J Med Internet Res
January 2025
Psychological Institute and Network Aging Research, Heidelberg University, Heidelberg, Germany.
Background: Immersive virtual reality (iVR) has emerged as a training method to prepare medical first responders (MFRs) for mass casualty incidents (MCIs) and disasters in a resource-efficient, flexible, and safe manner. However, systematic evaluations and validations of potential performance indicators for virtual MCI training are still lacking.
Objective: This study aimed to investigate whether different performance indicators based on visual attention, triage performance, and information transmission can be effectively extended to MCI training in iVR by testing if they can discriminate between different levels of expertise.
Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.
J Med Internet Res
January 2025
Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.
Background: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.
View Article and Find Full Text PDFEndovascular Approaches to Diagnosing Pelvic Varicose Veins in Men: Investigating Efficacy and Outcomes.
Surg Technol Int
January 2025
Department of Psychiatry and Narcology, I.M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, Russian Federation.
Pelvic Venous Disorder (PEVD) and May-Thurner syndrome (MTS) represent relatively understudied vascular issues that can significantly impact patients' quality of life. This study aims to evaluate the efficacy of surgical treatment for PEVD and MTS, conduct a comparative analysis of outcomes, and determine the practical significance of different therapeutic approaches. The study was conducted from 2019 to 2022 in Moscow, Russia, encompassing two outpatient clinics.
View Article and Find Full Text PDFDistinguishing benign and malignant myxoid soft tissue tumors: Performance of radiomics vs. radiologists.
PLoS One
January 2025
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Introduction: Benign and malignant myxoid soft tissue tumors have shared clinical, imaging, and histologic features that can make diagnosis challenging. The purpose of this study is comparison of the diagnostic performance of a radiomic based machine learning (ML) model to musculoskeletal radiologists.
Methods: Manual segmentation of 90 myxoid soft tissue tumors (45 myxomas and 45 myxofibrosarcomas) was performed on axial T1, and T2FS or STIR magnetic resonance imaging sequences.
A safe-enhanced fully closed-loop artificial pancreas controller based on deep reinforcement learning.
PLoS One
January 2025
Institute of Visual Informatics, The National University of Malaysia (UKM), Bangi, Malaysia.
Patients with type 1 diabetes and their physicians have long desired a fully closed-loop artificial pancreas (AP) system that can alleviate the burden of blood glucose regulation. Although deep reinforcement learning (DRL) methods theoretically enable adaptive insulin dosing control, they face numerous challenges, including safety and training efficiency, which have hindered their clinical application. This paper proposes a safe and efficient adaptive insulin delivery controller based on DRL.
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