Browsing by Subject "Surgical Skill Evaluation"
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Item Dynamic Discriminant Analysis with Applications in Computational Surgery(2017-05) Dockter, RodneyBackground: The field of computational surgery involves the use of new technologies to improve surgical safety and patient outcomes. Two open problems in this field include smart surgical tools for identifying tissues via backend sensing, and classifying surgical skill level using laparoscopic tool motion. Prior work in these fields has been impeded by the lack of a dynamic discriminant analysis technique capable of classifying data given systems with overwhelming similarity. Methods: Four new machine learning algorithms were developed (DLS, DPP, RELIEF-RBF, and Intent Vectors). These algorithms were then applied to the open problems within computational surgery. These algorithms are designed with the specific goal of finding regions of data with maximum discriminating information while ignoring regions of similarity or data scarcity. The results of these techniques are contrasted with current machine learning algorithms found in the literature. Results: For the tissue identification problem, results indicate that the proposed DLS algorithm provides better classification than existing methods. For the surgical skill evaluation problem, results indicate that the Intent Vectors approach provides equivalent or better classification accuracy when compared to prior art. Interpretation: The algorithms presented in this work provide a novel approach to the classification of time-series data for systems with overwhelming similarity by focusing on separability maximization while maintaining a tractable training routine and real-time classification for unseen data.Item Motion Analysis through Crowd-Sourced Assessment and Feature Design with Applications to Surgical Technical Skill Evaluation(2018-06) French, AnnaSurgical technical skill has a direct impact on patient health outcomes. Robotic surgical procedures present an opportunity for motion analysis-based skill assessment due to their readily available data streams detailing all manner of measurements about the tool motion. This proposes features that can help discern degrees of surgical skill. It also analyzes the importance of background contextual information in videos of surgical procedures, with regard to a crowd-sourced rater's ability to rate a surgeon's ability when background contextual information from a procedure is removed.