Reinforcement learning in surgery von Datta, Shounak, Li, Yanjun, Ruppert, Matthew M., Ren, Yuanfang, Shickel, Benjamin, Ozrazgat-Baslanti, Tezcan, Rashidi, Parisa, Bihorac, Azra

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Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis von Adiyeke, Esra, Ren, Yuanfang, Guan, Ziyuan, Ruppert, Matthew M., Rashidi, Parisa, Bihorac, Azra, Ozrazgat-Baslanti, Tezcan

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Intraoperative hypotension and postoperative acute kidney injury: A systematic review von Penev, Yordan, Ruppert, Matthew M., Bilgili, Ahmet, Li, Youlei, Habib, Raiya, Dozic, Abdul-Vehab, Small, Coulter, Adiyeke, Esra, Ozrazgat-Baslanti, Tezcan, Loftus, Tyler J., Giordano, Chris, Bihorac, Azra

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Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures von Ren, Yuanfang, Li, Yanjun, Loftus, Tyler J., Balch, Jeremy, Abbott, Kenneth L., Ruppert, Matthew M., Guan, Ziyuan, Shickel, Benjamin, Rashidi, Parisa, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra

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Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care von Loftus, Tyler J., Ruppert, Matthew M., Ozrazgat-Baslanti, Tezcan, Balch, Jeremy A., Shickel, Benjamin, Hu, Die, Efron, Philip A., Tighe, Patrick J., Hogan, William R., Rashidi, Parisa, Upchurch, Gilbert R., Bihorac, Azra

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Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension von Datta, Shounak, Loftus, Tyler J., Ruppert, Matthew M., Giordano, Chris, Upchurch, Gilbert R., Rashidi, Parisa, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra

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Improved predictive models for acute kidney injury with IDEA: Intraoperative Data Embedded Analytics von Adhikari, Lasith, Ozrazgat-Baslanti, Tezcan, Ruppert, Matthew, Madushani, R W M A, Paliwal, Srajan, Hashemighouchani, Haleh, Zheng, Feng, Tao, Ming, Lopes, Juliano M, Li, Xiaolin, Rashidi, Parisa, Bihorac, Azra

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A deep learning–based dynamic model for predicting acute kidney injury risk severity in postoperative patients von Adiyeke, Esra, Ren, Yuanfang, Ruppert, Matthew M., Shickel, Benjamin, Kane-Gill, Sandra L., Murugan, Raghavan, Rashidi, Parisa, Bihorac, Azra, Ozrazgat-Baslanti, Tezcan

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Risk-Specific Training Cohorts to Address Class Imbalance in Surgical Risk Prediction von Balch, Jeremy A, Ruppert, Matthew M, Guan, Ziyuan, Buchanan, Timothy R, Abbott, Kenneth L, Shickel, Benjamin, Bihorac, Azra, Liang, Muxuan, Upchurch, Gilbert R, Tignanelli, Christopher J, Loftus, Tyler J

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A framework for a consistent and reproducible evaluation of manual review for patient matching algorithms von Gupta, Agrayan K, Kasthurirathne, Suranga N, Xu, Huiping, Li, Xiaochun, Ruppert, Matthew M, Harle, Christopher A, Grannis, Shaun J

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Dynamic predictions of postoperative complications from explainable, uncertainty-aware, and multi-task deep neural networks von Shickel, Benjamin, Loftus, Tyler J., Ruppert, Matthew, Upchurch, Gilbert R., Ozrazgat-Baslanti, Tezcan, Rashidi, Parisa, Bihorac, Azra

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Aligning Patient Acuity With Resource Intensity After Major Surgery: A Scoping Review von Loftus, Tyler J., Balch, Jeremy A., Ruppert, Matthew M., Tighe, Patrick J., Hogan, William R., Rashidi, Parisa, Upchurch, Gilbert R., Bihorac, Azra

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Improving the Intensive Care Patient Experience With Virtual Reality-A Feasibility Study von Ong, Triton L, Ruppert, Matthew M, Akbar, Maisha, Rashidi, Parisa, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra, Suvajdzic, Marko

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Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients von Ozrazgat-Baslanti, Tezcan, Ren, Yuanfang, Adiyeke, Esra, Islam, Rubab, Hashemighouchani, Haleh, Ruppert, Matthew, Miao, Shunshun, Loftus, Tyler, Johnson-Mann, Crystal, Madushani, R W M A, Shenkman, Elizabeth A, Hogan, William, Segal, Mark S, Lipori, Gloria, Bihorac, Azra, Hobson, Charles

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Metabolomic Profiling for Diagnosis and Prognostication in Surgery: A Scoping Review von Khan, Tabassum A., Loftus, Tyler J., Filiberto, Amanda C., Ozrazgat-Baslanti, Tezcan, Ruppert, Matthew M., Bandyopadhyay, Sabyasachi, Laiakis, Evagelia C., Arnaoutakis, Dean J., Bihorac, Azra

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Electronic Health Record Data Quality and Performance Assessments: Scoping Review von Penev, Yordan P, Buchanan, Timothy R, Ruppert, Matthew M, Liu, Michelle, Shekouhi, Ramin, Guan, Ziyuan, Balch, Jeremy, Ozrazgat-Baslanti, Tezcan, Shickel, Benjamin, Loftus, Tyler J, Bihorac, Azra

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ICU Delirium-Prediction Models: A Systematic Review von Ruppert, Matthew M, Lipori, Jessica, Patel, Sandip, Ingersent, Elizabeth, Cupka, Julie, Ozrazgat-Baslanti, Tezcan, Loftus, Tyler, Rashidi, Parisa, Bihorac, Azra

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Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review von Balch, Jeremy A, Ruppert, Matthew M, Loftus, Tyler J, Guan, Ziyuan, Ren, Yuanfang, Upchurch, Gilbert R, Ozrazgat-Baslanti, Tezcan, Rashidi, Parisa, Bihorac, Azra

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Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform von Ren, Yuanfang, Loftus, Tyler J, Datta, Shounak, Ruppert, Matthew M, Guan, Ziyuan, Miao, Shunshun, Shickel, Benjamin, Feng, Zheng, Giordano, Chris, Upchurch, Jr, Gilbert R, Rashidi, Parisa, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra

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Predictive Modeling for Readmission to Intensive Care: A Systematic Review von Ruppert, Matthew M, Loftus, Tyler J, Small, Coulter, Li, Han, Ozrazgat-Baslanti, Tezcan, Balch, Jeremy, Holmes, Reed, Tighe, Patrick J, Upchurch, Jr, Gilbert R, Efron, Philip A, Rashidi, Parisa, Bihorac, Azra

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