Parsimonious machine learning models to predict resource use in cardiac surgery across a statewide collaborative by Verma, Arjun, Sanaiha, Yas, Hadaya, Joseph, Maltagliati, Anthony Jason, Tran, Zachary, Ramezani, Ramin, Shemin, Richard J., Benharash, Peyman, Benharash, Peyman, Shemin, Richard J., Satou, Nancy, Nguyen, Tom, Clary, Carolyn, Madani, Michael, Higgins, Jill, Steltzner, Dawna, Kiaii, Bob, Young, J. Nilas, Behan, Kathleen, Houston, Heather, Matsumoto, Cindi, Sun, Jack C., Flavin, Lisha, Fopiano, Patria, Cabrera, Maricel, Khaki, Rakan, Washabaugh, Polly

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Parsimonious machine learning models to predict resource use in cardiac surgery across a statewide collaborativeCentral MessagePerspective by Arjun Verma, Yas Sanaiha, MD, Joseph Hadaya, MD, Anthony Jason Maltagliati, MD, Zachary Tran, MD, Ramin Ramezani, PhD, Richard J. Shemin, MD, Peyman Benharash, MD, Peyman Benharash, MD, FACS, Richard J. Shemin, MD, FACS, Nancy Satou, Tom Nguyen, MD, Carolyn Clary, Michael Madani, MD, FACS, Jill Higgins, Dawna Steltzner, Bob Kiaii, MD, FRCSC, FACS, J. Nilas Young, MD, FACS, Kathleen Behan, Heather Houston, Cindi Matsumoto, Jack C. Sun, MD, MS, FRCSC, Lisha Flavin, Patria Fopiano, Maricel Cabrera, Rakan Khaki, MPH, Polly Washabaugh, BS

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