Machine learning techniques to examine large patient databases.

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Learning Credible Models (2017, background): “• formally defining credibility in the linear setting • proposing a novel regularization term EYE (expert yielded”
Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions (2016, background): “Moreover, ML techniques such as decision trees and forests, artificial neural networks, Bayesian networks, Support Vector Machines and Gaussian processes [160] could discover and evaluate operating techniques that do not yet belong to, but could potentially outperform current surgical practice.”
Automated annotation and classification of BI-RADS assessment from radiology reports (2017, unknown): “We chose NB because it is the simplest type of Bayesian network and makes the assumption of conditional independence of the predictors on the target variable [37,40].”