Currently, in radiology, qualified physicians visually gauge medical images and report findings to detect, characterize, and scrutinize diseases. The assessment is mainly based on education and experience and can be, at times, skewed. The difference is that AI excels at recognizing complex patterns in imaging data and can provide a quantitative assessment in an automated fashion. More accurate and reproducible radiology assessments can then be made when AI is integrated into the clinical workflow as a tool to assist medical practitioners.  Radiographic images, in combination with data on clinical outcomes, have created the expansion of radiomics where they have integrated deep learning to learn feature representations automatically from images.

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