Here, we show that extrinsic background can significantly affect a classification model using Raman images, yielding misleadingly high accuracies in the distinction of benign and malignant samples of ...

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DeBakey Veterans Affairs Medical Center and Section of Health Services Research ... dean.f.sittig{at}uth.tmc.edu Background Conceptual models have been developed to address challenges inherent in ...

In states that choose to end expanded Medicaid eligibility, fewer covered beneficiaries mean hospitals will see less ...

Abstract: Various hierarchical CNN networks have proven their effectiveness in the field of medical image segmentation ... and suppress irrelevant background information. We train the model on the ...

But, in response, a cross-party group of MPs with medical and clinical backgrounds have appealed to colleagues in Parliament to support a Bill they say is coming back to the Commons with ...

Abstract: Precise medical image segmentation is important for automating diagnosis and treatment planning in healthcare. While images present the most significant information for segmenting organs ...

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An upgraded version of Google’s medical chatbot can use smartphone photos to diagnose rashes and can evaluate a host of other types of medical imagery — improving the bot’s ability to ...

The authors of an editorial published in the American Journal of Hematology, claim that "generative Artificial Intelligence can be exploited to produce fraudulent scientific images, either from ...