Sepsis accounts for a substantial portion of global deaths and healthcare costs. The objective of this reproducibility study is to validate Duke Health’s Sepsis Watch ML model, in a new community healthcare setting and…
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Embodied artificial intelligence (EAI) integrates perception, memory, reasoning and action through physical interaction, enabling multimodal dynamic learning and real-time feedback. In ophthalmology, EAI supports data-driven decision-making, improving the precision and personalization of diagnosis, surgery,…
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Lila Sciences is developing an AI-enabled scientific superintelligence platform—paired with autonomous labs—that can run the entire scientific method.In a conversation with MobiHealthNews, Molly Gibson, president of future science at Lila Sciences, explained that this…
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Thalassemia is an inherited blood disorder. Current diagnostic methods mainly rely on sophisticated equipment and specifically trained technicians. This study aims to identify and genotype thalassemia by applying machine learning (ML) algorithms to routine…
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Retinal age has emerged as a promising biomarker of aging, offering a non-invasive and accessible assessment tool. We developed a deep learning model to estimate retinal age with enhanced accuracy, leveraging retinal images from…
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The NHS Confederation and Beamtree have partnered to roll out an AI and machine learning analytics platform aimed at helping hospitals to forecast future trends.
The Evolve Collaborative is a nationwide collaborative of healthcare leaders,…
Phenotypic information for cancer research is embedded in unstructured electronic health records (EHR), requiring effort to extract. Deep learning models can automate this but face scalability issues due to privacy concerns. We evaluated techniques…
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#HIMSS25Europe kicks off tomorrow and our team is already on the ground in Paris.With three days of action-packed learning ahead, Tjasa and Susanna took a moment on the main stage at Palais des Congrès…
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Under-resourced hospitals face a big artificial intelligence adoption learning curve, but it’s surmountable if they can keep up with rapidly advancing analytics and AI tools in an industry increasingly turning to automation to lower…
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In acute ischemic stroke due to large-vessel occlusion (AIS-LVO), late-window endovascular thrombectomy (EVT) decisions depend on penumbra-to-core (P:C) mismatch from computed tomographic perfusion (CTP). We developed multiple machine learning (ML) models to predict P:C…
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