Artificial intelligence (AI) is being introduced into healthcare through clinical imaging analysis and embedded in algorithms inside medical devices. Whether diagnostician, radiologist, or oncologist, a significant part of the life of a physician is spent examining images and writing reports about them; therefore, currently the bulk of commercial activity in AI in healthcare is in imaging analysis. There is a huge opportunity to augment physicians with AI-based systems that can reduce the workload across protocoling, imaging analysis, and automated reporting of the results — ultimately improving productivity with AI.
This report delves into many advances in clinical imaging being introduced through AI. The activity today is mostly focused on working with the current computational environment that exists in the radiologist’s laboratory, and examines how advanced medical instruments and software solutions that incorporate AI can augment a radiologist’s work. The end goal could be an integrated system that replaces much of the legacy equipment and assists in: performing scans, analyzing images, and producing reports through one connected solution.
Download the new white paper from NVIDIA that explores increasing productivity with AI and how tools like deep learning can enhance offerings and cut down on cost.
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