In healthcare, federated learning (FL) is emerging as a methodology to enable the analysis of large and disparate datasets while allowing custodians to retain sovereignty. While FL minimises data-sharing challenges, concerns surrounding ethics, privacy,…
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With the shift toward de-escalating surgery in breast cancer, prediction models incorporating imaging can reassess the need for surgical axillary staging. This study employed advancements in deep learning to comprehensively evaluate routine mammograms for…
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Cognitive bias accounts for a significant portion of preventable errors in healthcare, contributing to significant patient morbidity and mortality each year. As large language models (LLMs) are introduced into healthcare and clinical decision-making, these…
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Medical image segmentation is vital for accurate diagnosis. While U-Net-based models are effective, they struggle to capture long-range dependencies in complex anatomy. We propose GH-UNet, a Group-wise Hybrid Convolution-ViT model within the U-Net framework,…
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Healthcare Cybersecurity Is Also a Clinical Concern
When a ransomware attack hampers a hospital’s electronic health records, the ripple effects are immediate and potentially life-threatening with diagnostic delays, canceled procedures and disrupted prescriptions. Every second…
Endoscopic interventions are essential for diagnosing and treating gastrointestinal conditions. Accurate and comprehensive documentation is crucial for enhancing patient safety and optimizing clinical outcomes; however, adverse events remain underreported. This study evaluates a machine…
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The applicability of vision-language models (VLMs) for acute care in emergency and intensive care units remains underexplored. Using a multimodal dataset of diagnostic questions involving medical images and clinical context, we benchmarked several small…
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Table of Contents
Introduction to Healthcare Cloud Migration
Tufts Medicine: Pioneering Epic EHR Cloud Migration
Baptist Memorial: Large-Scale Cloud Transformation
Key Benefits of EHR Cloud Migration
Implementation Timeline and Process
Cost Optimization and Performance Gains
Future of Healthcare Cloud Computing
Conclusion
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Introduction…
Exergames are emerging tools for cognitive-motor neurorehabilitation, but their effects in adults with neurological conditions remain insufficiently explored. This systematic review examined studies from PubMed, Scopus, Embase, and Web of Science, assessing the impact…
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Rare gynecological tumors (RGTs) present major clinical challenges due to their low incidence and heterogeneity. The lack of clear guidelines leads to suboptimal management and poor prognosis. Molecular tumor boards accelerate access to effective…
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