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Exploring Virtual Reality and Exercise Simulator Interventions in Patients With Attention Deficit Hyperactivity Disorder: Comprehensive Literature Review.
JMIR Serious Games
January 2025
School of Computing, Engineering and Mathematical Sciences, Optus Chair Digital Health, La Trobe University, Melbourne, Australia.
Background: This review explores virtual reality (VR) and exercise simulator-based interventions for individuals with attention-deficit/hyperactivity disorder (ADHD). Past research indicates that both VR and simulator-based interventions enhance cognitive functions, such as executive function and memory, though their impacts on attention vary.
Objective: This study aimed to contribute to the ongoing scientific discourse on integrating technology-driven interventions into the management and evaluation of ADHD.
Improved Outcomes and Resource Use With Normothermic Machine Perfusion in Liver Transplantation.
JAMA Surg
January 2025
Division of Transplant Surgery, Department of Surgery, Mayo Clinic Arizona, Phoenix.
Importance: Normothermic machine perfusion (NMP) has been shown to reduce peritransplant complications. Despite increasing NMP use in liver transplant (LT), there is a scarcity of real-world clinical experience data.
Objective: To compare LT outcomes between donation after brain death (DBD) and donation after circulatory death (DCD) allografts preserved with NMP or static cold storage (SCS).
A Mechanical Construction to Enhance the Stability and Safety of Lifting and Thrusting Manipulation of Acupuncture.
J Vis Exp
January 2025
School of Acupuncture-Moxibustion and Tuina, Shanghai University of Traditional Chinese Medicine;
The therapeutic effectiveness of acupuncture relies on both safety and stability, making these factors essential in acupuncture manipulation research. However, manual manipulation introduces unavoidable inaccuracies, which can impact the reliability of research findings. To address this challenge, a unique lifting and thrusting manipulation control cannula was designed in this study, offering flexible adjustment of movement amplitude.
View Article and Find Full Text PDFGenerative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments.
Eur J Nucl Med Mol Imaging
January 2025
Department of Biomedical Imaging and Image-guided Therapy, Division of Nuclear Medicine, Medical University of Vienna, Spitalgasse 23, Vienna, 1090, Austria.
Purpose: Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.
Methods: We trained a generative model on Tc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis.
Optimizing Sedation Strategies in the Cardiac ICU: Induction, Maintenance and Weaning.
Curr Cardiol Rep
January 2025
Cardiovascular Division, University of Minnesota, 420 Delaware Street SE, MMC 508, Minneapolis, MN, 55455, USA.
Purpose Of Review: We aim to summarize the available literature guiding tailored sedation practices for specific conditions encountered in the Cardiovascular Intensive Care Unit (CICU).
Recent Findings: Data specific for the CICU population is lacking. Preclinical data and observational studies guide sedation approaches for specific pathologies that we have used to generate a guideline for sedative choice for various scenarios.
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