Abstract
There are many applications of artificial intelligence (AI) in medicine, however, few clinicians have familiarity or experience with them. Machine learning, a subset of AI, is the use of computers to “learn” and improve performance based on data provided without programming (1). Data are analyzed based on labeled outcomes in so-called supervised learning. Deep learning is computationally more complex and is said to mimic the human brain with interactions involving artificial neural networks. These methods suffer from a “black box” phenomenon that is poorly understood by clinicians, other than those who have a strong knowledge of computer science.
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