Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Scott M. Pappada"'
Autor:
Alexander J. Didier, Anthony Nigro, Zaid Noori, Mohamed A. Omballi, Scott M. Pappada, Danae M. Hamouda
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
IntroductionMachine learning (ML) techniques have gained increasing attention in the field of healthcare, including predicting outcomes in patients with lung cancer. ML has the potential to enhance prognostication in lung cancer patients and improve
Externí odkaz:
https://doaj.org/article/0c8270d3c0d2490fb8a018320d2515a3
Autor:
Scott M. Pappada, Thomas J. Papadimos, Sadik Khuder, Sean T. Mack, Peyton Z. Beachy, Andrew B. Casabianca
Publikováno v:
Anesthesiology Research and Practice, Vol 2022 (2022)
The operating room (OR) is considered a major cost center and revenue generator for hospitals. Multiple factors contribute to OR delays and impact patient safety, patient satisfaction scores, and hospital financial performance. Reducing OR delays all
Externí odkaz:
https://doaj.org/article/832000307a0e468fa8592e80c55e1d9f
Publikováno v:
Clinical Case Reports, Vol 7, Iss 10, Pp 1984-1988 (2019)
Abstract Antiphospholipid syndrome (APS) is an autoimmune disease that demonstrates antiphospholipid antibodies that cause hypercoagulability and leads to venous and arterial thrombosis. Autoantibodies to a disintegrin‐like and metalloprotease with
Externí odkaz:
https://doaj.org/article/c3ad6ac7f4ad439f95da7d7eca19021b
Autor:
Scott M. Pappada, Karina Woodling, Mohammad Hamza Owais, Evan M. Zink, Layth Dahbour, Ravi S. Tripathi, Sadik A. Khuder, Thomas J. Papadimos
Publikováno v:
BMC Research Notes, Vol 11, Iss 1, Pp 1-5 (2018)
Abstract Objective Hyperglycemia is an independent risk factor in hospitalized patients for adverse outcomes, even if patients are not diabetic. We used continuous glucose monitoring to evaluate whether glycemic control (hyperglycemia) in the first 7
Externí odkaz:
https://doaj.org/article/3158a6d6e7e8404ca8b39b4c70b3cbbc
Autor:
Mohammad Hamza Owais, Brent D. Cameron, Juan Carlos Jaume, Ravi S. Tripathi, Ana Mavarez-Martinez, Scott M. Pappada, Thomas J Papadimos
Publikováno v:
Diabetes Technology & Therapeutics. 22:383-394
Background: Achieving glycemic control in critical care patients is of paramount importance, and has been linked to reductions in mortality, intensive care unit (ICU) length of stay, and morbiditie...
Autor:
Scott M Pappada
Publikováno v:
Journal of cardiac surgeryREFERENCES. 36(11)
Machine learning and artificial intelligence (AI) have arrived in medicine and the healthcare community is experiencing significant growth in their adoption across numerous patient care settings. There are countless applications for machine learning
Publikováno v:
Clinical Case Reports
Clinical Case Reports, Vol 7, Iss 10, Pp 1984-1988 (2019)
Clinical Case Reports, Vol 7, Iss 10, Pp 1984-1988 (2019)
Antiphospholipid syndrome (APS) is an autoimmune disease that demonstrates antiphospholipid antibodies that cause hypercoagulability and leads to venous and arterial thrombosis. Autoantibodies to a disintegrin‐like and metalloprotease with thrombos
Autor:
Andrew B. Casabianca, James S Papadimos, Michael R Lyaker, Thomas J. Papadimos, Scott M. Pappada
The flight of refugees has been part of the human condition since the beginning of time. Recent events in the Middle East have caused a mass migration of refugees from Syria, Iraq, and Afghanistan. Their primary destination has been Europe, more spec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24a000aa31aa2969bdad485128656b69
https://doi.org/10.5772/intechopen.91210
https://doi.org/10.5772/intechopen.91210
Publikováno v:
Journal of Pharmaceutical Innovation. 14:341-358
The purpose of this research was to develop a system that can read and report the volume of liquid medication present in syringes. The system is comprised of a digital webcam which is designed to communicate with a computer program developed using MA
Publikováno v:
Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care. 7:232-236
Physiological data collection methods are unobtrusive, passive, continuous, and objective. The information afforded by sensors collecting physiological data can be transformed to represent operator performance estimates and stress state visualization