Development of An Individualized Risk Prediction Model for COVID-19 Using Electronic Health Record Data. - Tarun Karthik Kumar Mamidi; Thi K. Tran-Nguyen; Ryan L. Melvin; Elizabeth A. Worthey (Frontiers Big Data, 2021)

Artificial Intelligence in Perioperative Medicine: A Proposed Common Language With Applications to FDA-Approved Devices. - Ryan L. Melvin; Matthew G. Broyles; Elizabeth W. Duggan; Sonia John; Andrew D. Smith; Dan E. Berkowitz (Frontiers Digit. Health, 2022)

Strengths-weaknesses-opportunities-threats analysis of artificial intelligence in anesthesiology and perioperative medicine. - Henry J. Paiste; Ryan Godwin; Andrew D. Smith; Dan E. Berkowitz; Ryan L. Melvin (Frontiers Digit. Health, 2024)

Grant drafting support with guided generative AI software. - Ryan Godwin; Jennifer J. DeBerry; Brant M. Wagener; Dan E. Berkowitz; Ryan L. Melvin (SoftwareX, 2024)

Toward efficient data science: A comprehensive MLOps template for collaborative code development and automation. - Ryan Godwin; Ryan L. Melvin (SoftwareX, 2024)

IRB-draft-generator: A generative AI tool to streamline the creation of institutional review board applications. - Ryan Godwin; Ayesha S. Bryant; Brant M. Wagener; Timothy J. Ness; Jennifer J. DeBerry; LaShun L. Horn; Shanna H. Graves; Ashley C. Archer; Ryan L. Melvin (SoftwareX, 2024)

Machine Learning Predicts Unplanned Care Escalations for Post-Anesthesia Care Unit Patients during the Perioperative Period: A Single-Center Retrospective Study. - Andrew B. Barker; Ryan L. Melvin; Ryan Godwin; David Benz; Brant M. Wagener (J. Medical Syst., 2024)