Publisher's Synopsis
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The first surgical AI guide of its kind! Machine learning, neural networks, and computer vision for surgical education, practice, and research
While radiology and pathology are on the leading edge of AI in healthcare, surgery is showing tremendous potential for disruption by AI. Written for anyone not steeped in mathematics, technology, or engineering, this matchless guide gets ahead of the knowledge curve now-so you can evaluate new technologies with a critical eye and make informed decisions about bringing AI into your practice.
Artificial Intelligence in Surgery covers the history, principles, and main subfields of AI, offering examples of current and near-future use cases for AI in surgery. It gives you a clear understanding of the ethical implications of AI, its potential impact on healthcare policy, and how to read and interpret papers that use AI. The appendix includes a quick reference on AI techniques, their use cases, strengths, and limitations; glossary of terms; important learning resources; and techniques (including examples of appropriate use cases, advantages, and limitations)-all of which can be used to interpret claims made by studies or companies using AI.
