Search Results - "Pappada, Scott M"

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  1. 1

    Contributing Factors to Operating Room Delays Identified from an Electronic Health Record: A Retrospective Study by Pappada, Scott M., Papadimos, Thomas J., Khuder, Sadik, Mack, Sean T., Beachy, Peyton Z., Casabianca, Andrew B.

    Published in Anesthesiology research and practice (13-09-2022)
    “…The operating room (OR) is considered a major cost center and revenue generator for hospitals. Multiple factors contribute to OR delays and impact patient…”
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    Journal Article
  2. 2

    Application of machine learning for lung cancer survival prognostication-A systematic review and meta-analysis by Didier, Alexander J, Nigro, Anthony, Noori, Zaid, Omballi, Mohamed A, Pappada, Scott M, Hamouda, Danae M

    “…Machine learning (ML) techniques have gained increasing attention in the field of healthcare, including predicting outcomes in patients with lung cancer. ML…”
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    Journal Article
  3. 3

    Presumed antiphospholipid syndrome and thrombotic thrombocytopenic purpura: An infrequent association by Dolin, Hallie Hanna, Dziuba, Mark, Pappada, Scott M., Papadimos, Thomas John

    Published in Clinical case reports (01-10-2019)
    “…Antiphospholipid syndrome (APS) is an autoimmune disease that demonstrates antiphospholipid antibodies that cause hypercoagulability and leads to venous and…”
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    Journal Article
  4. 4

    Machine learning in medicine: It has arrived, let's embrace it by Pappada, Scott M.

    Published in Journal of cardiac surgery (01-11-2021)
    “…Machine learning and artificial intelligence (AI) have arrived in medicine and the healthcare community is experiencing significant growth in their adoption…”
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    Journal Article
  5. 5

    Continuous glucose monitoring identifies relationship between optimized glycemic control and post-discharge acute care facility needs by Pappada, Scott M, Woodling, Karina, Owais, Mohammad Hamza, Zink, Evan M, Dahbour, Layth, Tripathi, Ravi S, Khuder, Sadik A, Papadimos, Thomas J

    Published in BMC research notes (31-07-2018)
    “…Hyperglycemia is an independent risk factor in hospitalized patients for adverse outcomes, even if patients are not diabetic. We used continuous glucose…”
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    Journal Article
  6. 6

    Evaluation of a model for glycemic prediction in critically ill surgical patients by Pappada, Scott M, Cameron, Brent D, Tulman, David B, Bourey, Raymond E, Borst, Marilyn J, Olorunto, William, Bergese, Sergio D, Evans, David C, Stawicki, Stanislaw P A, Papadimos, Thomas J

    Published in PloS one (19-07-2013)
    “…We evaluated a neural network model for prediction of glucose in critically ill trauma and post-operative cardiothoracic surgical patients. A prospective,…”
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    Journal Article
  7. 7

    Neural network-based real-time prediction of glucose in patients with insulin-dependent diabetes by Pappada, Scott M, Cameron, Brent D, Rosman, Paul M, Bourey, Raymond E, Papadimos, Thomas J, Olorunto, William, Borst, Marilyn J

    Published in Diabetes technology & therapeutics (01-02-2011)
    “…Continuous glucose monitoring (CGM) technologies report measurements of interstitial glucose concentration every 5 min. CGM technologies have the potential to…”
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    Journal Article
  8. 8

    Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study by Pappada, Scott M., Owais, Mohammad Hamza, Feeney, John J., Salinas, Jose, Chaney, Benjamin, Duggan, Joan, Sparkle, Tanaya, Aouthmany, Shaza, Hinch, Bryan, Papadimos, Thomas J.

    Published in Anaesthesia critical care & pain medicine (01-12-2024)
    “…Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality…”
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    Journal Article
  9. 9

    Development of a neural network for prediction of glucose concentration in type 1 diabetes patients by Pappada, Scott M, Cameron, Brent D, Rosman, Paul M

    Published in Journal of diabetes science and technology (01-09-2008)
    “…A major difficulty in the management of diabetes is the optimization of insulin therapies to avoid occurrences of hypoglycemia and hyperglycemia. Many factors…”
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    Journal Article
  10. 10

    Development of a neural network model for predicting glucose levels in a surgical critical care setting by Pappada, Scott M, Borst, Marilyn J, Cameron, Brent D, Bourey, Raymond E, Lather, Jason D, Shipp, Desmond, Chiricolo, Antonio, Papadimos, Thomas J

    Published in Patient safety in surgery (09-09-2010)
    “…Development of neural network models for the prediction of glucose levels in critically ill patients through the application of continuous glucose monitoring…”
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    Journal Article
  11. 11

    Comorbidity polypharmacy score and its clinical utility: A pragmatic practitioner's perspective by Stawicki, Stanislaw P, Kalra, Sarathi, Jones, Christian, Justiniano, Carla F, Papadimos, Thomas J, Galwankar, Sagar C, Pappada, Scott M, Feeney, John J, Evans, David C

    Published in Journal of emergencies, trauma and shock (01-10-2015)
    “…Modern medical management of comorbid conditions has resulted in escalating use of multiple medications and the emergence of the twin phenomena of…”
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    Journal Article
  12. 12

    Increasing patient safety with neonates via handoff communication during delivery: a call for interprofessional health care team training across GME and CME by Vanderbilt, Allison A, Pappada, Scott M, Stein, Howard, Harper, David, Papadimos, Thomas J

    Published in Advances in medical education and practice (01-01-2017)
    “…Hospitals have struggled for years regarding the handoff process of communicating patient information from one health care professional to another. Ineffective…”
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    Journal Article
  13. 13

    System decision framework for augmenting human performance using real-time workload classifiers by Durkee, Kevin T., Pappada, Scott M., Ortiz, Andres E., Feeney, John J., Galster, Scott M.

    “…The high volume of information available to human operators and increasing scale of work can become unmanageable due to the complexity found in a variety of…”
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    Conference Proceeding
  14. 14

    A System for Real-Time Syringe Classification and Volume Measurement Using a Combination of Image Processing and Artificial Neural Networks by Regmi, Hem K., Nesamony, Jerry, Pappada, Scott M., Papadimos, Thomas J., Devabhaktuni, Vijay

    Published in Journal of pharmaceutical innovation (01-12-2019)
    “…Purpose The purpose of this research was to develop a system that can read and report the volume of liquid medication present in syringes. Methods The system…”
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    Journal Article
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    Comorbidity polypharmacy score and its clinical utility: A pragmatic practitioner′s perspective by Stawicki, StanislawP, Kalra, Sarathi, Jones, Christian, Justiniano, CarlaF, Papadimos, ThomasJ, Galwankar, SagarC, Pappada, ScottM, Feeney, JohnJ, Evans, DavidC

    “…Modern medical management of comorbid conditions has resulted in escalating use of multiple medications and the emergence of the twin phenomena of…”
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    Journal Article
  17. 17