Publications by authors named "Vamsi Thiriveedhi"

Artificial intelligence (AI) algorithms hold the potential to revolutionize radiology. However, a significant portion of the published literature lacks transparency and reproducibility, which hampers sustained progress toward clinical translation. Although several reporting guidelines have been proposed, identifying practical means to address these issues remains challenging.

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Rapid advances in medical imaging Artificial Intelligence (AI) offer unprecedented opportunities for automatic analysis and extraction of data from large imaging collections. Computational demands of such modern AI tools may be difficult to satisfy with the capabilities available on premises. Cloud computing offers the promise of economical access and extreme scalability.

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Public imaging datasets are critical for the development and evaluation of automated tools in cancer imaging. Unfortunately, many do not include annotations or image-derived features, complicating downstream analysis. Artificial intelligence-based annotation tools have been shown to achieve acceptable performance and can be used to automatically annotate large datasets.

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The remarkable advances of artificial intelligence (AI) technology are revolutionizing established approaches to the acquisition, interpretation, and analysis of biomedical imaging data. Development, validation, and continuous refinement of AI tools requires easy access to large high-quality annotated datasets, which are both representative and diverse. The National Cancer Institute (NCI) Imaging Data Commons (IDC) hosts large and diverse publicly available cancer image data collections.

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Background: Many states in the United States have progressed towards legalization of marijuana including decriminalization, medicinal and/or recreational use. We studied the impact of legalization on cannabis-related emergency department visits in states with varying degrees of legalization.

Methods: Seventeen healthcare institutions in fifteen states (California, Colorado, Connecticut, Florida, Iowa, Kentucky, Maryland, Massachusetts, Missouri, New Hampshire, Oregon, South Carolina, Tennessee, Texas, Washington) participated.

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