Technology and its Impact on Patient Care
Peter Schulam, MD, PhD, argues that adopting robotic assisted surgery into urological practices can reduce medical errors and surgeon performance variability. Furthermore, he explains the need for larger and more structured medical data sets. This will enable machine learning when developing artificial intelligence (AI) to enhance prognostic and diagnostic accuracy, cancer mortality prediction, and interpretation of digitized images.
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