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Full-Text Articles in Medicine and Health Sciences
A Machine Learning Approach To First Pass Reperfusion In Mechanical Thrombectomy: Prediction And Feature Analysis., Lohit Velagapudi, Nikolaos Mouchtouris, Richard F Schmidt, David Vuong, Omaditya Khanna, Ahmad Sweid, Bryan Sadler, Fadi Al-Saiegh, M Reid Gooch, Pascal Jabbour, Robert H Rosenwasser, Stavropoula Tjoumakaris
A Machine Learning Approach To First Pass Reperfusion In Mechanical Thrombectomy: Prediction And Feature Analysis., Lohit Velagapudi, Nikolaos Mouchtouris, Richard F Schmidt, David Vuong, Omaditya Khanna, Ahmad Sweid, Bryan Sadler, Fadi Al-Saiegh, M Reid Gooch, Pascal Jabbour, Robert H Rosenwasser, Stavropoula Tjoumakaris
Department of Neurosurgery Faculty Papers
INTRODUCTION: Novel machine learning (ML) methods are being investigated across medicine for their predictive capabilities while boasting increased adaptability and generalizability. In our study, we compare logistic regression with machine learning for feature importance analysis and prediction in first-pass reperfusion.
METHODS: We retrospectively identified cases of ischemic stroke treated with mechanical thrombectomy (MT) at our institution from 2012-2018. Significant variables used in predictive modeling were demographic characteristics, medical history, admission NIHSS, and stroke characteristics. Outcome was binarized TICI on first pass (0-2a vs 2b-3). Shapley feature importance plots were used to identify variables that strongly affected outcomes.
RESULTS: Accuracy for …