Generative AI has the potential to transform patient care, but it can also wreak havoc if left unattended.
By Paul Cerrato, MA, senior research analyst and communications specialist and John Halamka, M.D., Diercks President, Mayo…
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Transforming AI Development Infrastructure
NVIDIA has unveiled its groundbreaking DGX Cloud Lepton marketplace, transforming how artificial intelligence developers access global GPU resources. This innovative platform connects AI developers with leading cloud providers including Lambda, CoreWeave,…
How ANNs Are Revolutionizing Medicine
Artificial Neural Networks (ANNs) have been quietly evolving since the 1950s, but their impact on healthcare has accelerated dramatically in recent years. Unlike modern Large Language Models (LLMs) like ChatGPT,…
Unlike their more modern large language model counterparts, artificial neural networks require human input to learn and function.ANNs have been around since the 1950s. They started taking hold in healthcare in the 1990s. Within…
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Adam Hesse, CEO, at Full Spectrum
The emerging technologies hype cycle had multiple AI applications at the peak of inflated expectations in 2023 and were just beginning the ride down to the Trough of Disillusionment…
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In part 2 of our series on the basics of digital technology, we explore the deep learning tools that can improve medical image analysis and much more.
By John Halamka, M.D., President, Mayo Clinic Platform…
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In this new series, we pull back the curtain on the Wizard of Oz to provide plain English explanations about machine learning, artificial neural networks, natural language processing, large language models, and related technology.
By Paul…
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Healthcare-associated infections (HAIs) from multi-drug resistant organisms (MDROs) pose a significant challenge for healthcare systems. Patients can arrive at hospitals already infected (“importation”) or acquire infections during their stay (“nosocomial infection”). Many cases, often…
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Remote monitoring is essential for healthcare digital transformation, however, this poses greater burdens on healthcare providers to review and respond as the data collected expands. This study developed a multimodal neural network to automate…
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This systematic review explores machine learning (ML) applications in surgical motion analysis using non-optical motion tracking systems (NOMTS), alone or with optical methods. It investigates objectives, experimental designs, model effectiveness, and future research directions….
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