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Scott M Pappada

Showing results (1-10 of 15) with videos related to

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Journal of Cardiac Surgery|August 15, 2021
Machine learning in medicine: It has arrived, let's embrace itScott M Pappada
Anaesthesia, Critical Care & Pain Medicine|December 1, 2025
Machine Learning and the Fourth Industrial Revolution: Transforming Immunocompromise Assessment in Critical CareScott M Pappada, Thomas J Papadimos, Guillame Dumas
Cureus|February 25, 2026
Insights From Michael Polanyi: Tacit Knowledge and Its Critical Importance in Medical EducationThomas J Papadimos, Justin Hsu, Scott M Pappada
Journal of Diabetes Science and Technology|November 4, 2009
Development of a neural network for prediction of glucose concentration in type 1 diabetes patientsScott M Pappada, Brent D Cameron, Paul M Rosman
Clinical Case Reports|October 19, 2019
Presumed antiphospholipid syndrome and thrombotic thrombocytopenic purpura: An infrequent associationHallie Hanna Dolin, Mark Dziuba, Scott M Pappada, et al.
Advances in Medical Education and Practice|June 28, 2017
Increasing patient safety with neonates via handoff communication during delivery: a call for interprofessional health care team training across GME and CMEAllison A Vanderbilt, Scott M Pappada, Howard Stein, et al.
Frontiers in Artificial Intelligence|April 22, 2024
Application of machine learning for lung cancer survival prognostication-A systematic review and meta-analysisAlexander J Didier, Anthony Nigro, Zaid Noori, et al.
Anesthesiology Research and Practice|September 23, 2022
Contributing Factors to Operating Room Delays Identified from an Electronic Health Record: A Retrospective StudyScott M Pappada, Thomas J Papadimos, Sadik Khuder, et al.
BMC Research Notes|August 2, 2018
Continuous glucose monitoring identifies relationship between optimized glycemic control and post-discharge acute care facility needsScott M Pappada, Karina Woodling, Mohammad Hamza Owais, et al.
Diabetes Technology & Therapeutics|February 3, 2011
Neural network-based real-time prediction of glucose in patients with insulin-dependent diabetesScott M Pappada, Brent D Cameron, Paul M Rosman, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Journal of Cardiac Surgery|August 15, 2021
Machine learning in medicine: It has arrived, let's embrace itScott M Pappada
Anaesthesia, Critical Care & Pain Medicine|December 1, 2025
Machine Learning and the Fourth Industrial Revolution: Transforming Immunocompromise Assessment in Critical CareScott M Pappada, Thomas J Papadimos, Guillame Dumas
Cureus|February 25, 2026
Insights From Michael Polanyi: Tacit Knowledge and Its Critical Importance in Medical EducationThomas J Papadimos, Justin Hsu, Scott M Pappada
Journal of Diabetes Science and Technology|November 4, 2009
Development of a neural network for prediction of glucose concentration in type 1 diabetes patientsScott M Pappada, Brent D Cameron, Paul M Rosman
Clinical Case Reports|October 19, 2019
Presumed antiphospholipid syndrome and thrombotic thrombocytopenic purpura: An infrequent associationHallie Hanna Dolin, Mark Dziuba, Scott M Pappada, et al.
Advances in Medical Education and Practice|June 28, 2017
Increasing patient safety with neonates via handoff communication during delivery: a call for interprofessional health care team training across GME and CMEAllison A Vanderbilt, Scott M Pappada, Howard Stein, et al.
Frontiers in Artificial Intelligence|April 22, 2024
Application of machine learning for lung cancer survival prognostication-A systematic review and meta-analysisAlexander J Didier, Anthony Nigro, Zaid Noori, et al.
Anesthesiology Research and Practice|September 23, 2022
Contributing Factors to Operating Room Delays Identified from an Electronic Health Record: A Retrospective StudyScott M Pappada, Thomas J Papadimos, Sadik Khuder, et al.
BMC Research Notes|August 2, 2018
Continuous glucose monitoring identifies relationship between optimized glycemic control and post-discharge acute care facility needsScott M Pappada, Karina Woodling, Mohammad Hamza Owais, et al.
Diabetes Technology & Therapeutics|February 3, 2011
Neural network-based real-time prediction of glucose in patients with insulin-dependent diabetesScott M Pappada, Brent D Cameron, Paul M Rosman, et al.
Pageof 2