Daniel Byrne is an award-winning author, teacher, and faculty member at Johns Hopkins University’s Whiting School of Engineering and the Department of Biostatistics at the Bloomberg School of Public Health. With more than 40 years of experience in artificial intelligence (AI) and predictive modeling in healthcare, his work focuses on improving patient outcomes using AI-driven solutions. Byrne holds a bachelor’s degree in biology and computer science from the University at Albany and a master’s degree in biostatistics from New York Medical College. His career began in 1983 when his team at New York Medical College demonstrated that personal computers were powerful enough to build and run AI tools in medicine, such as the “Automated Physiologic Profile”. This innovation allowed surgeons to operate safely on older patients. He then developed a state-of-the-art trauma registry and showed that by creating a structured, multi-hospital database, it was possible to use AI tools to improve the care of trauma patients. After 6 years at New York Medical College, Byrne decided to start his own AI consulting business – Byrne Research, in Ridgefield, CT. During the next 10 years, he collaborated with medical researchers and pharmaceutical companies developing and testing various AI predictive models. His first book “Publishing Your Medical Research” led to a faculty position at Vanderbilt and a move to Nashville, TN where he worked as a faculty member in the Department of Biostatistics for 24 years. In his role as Director of Artificial Intelligence Research at Vanderbilt, he gained broad experience in creating, implementing, and testing AI tools in a hospital setting. His team created AI tools to predict hospital readmissions, pressure ulcers, postpartum hemorrhage, autoimmune disease, COVID-19, and blood clots. Based on this rich experience, Byrne published his second book “Artificial Intelligence for Improved Patient Outcomes – Moving Forward with Rigorous Science”. His specific area of expertise is in how to evaluate AI in pragmatic randomized controlled trials and publish the results in high-impact journals. Byrne has now published more than 165 papers and will use this experience to teach you how to raise the bar with AI evaluations so that you can publish your findings in the top medical journals. In 2024, he moved to Maryland and became a faculty member at Johns Hopkins University, where he teaches AI in Healthcare.

Education History

  • B.A., Biology and Computer Science, University at Albany, State University of New York
  • M.S., Biostatistics, New York Medical College

Work Experience

Instructor, JHU Whiting School of Engineering

Publications

Books:
“Artificial Intelligence for Improved Patient Outcomes – Principles for Moving Forward with Rigorous Science”.
https://www.amazon.com/dp/1975197933/

“Publishing Your Medical Research”
https://www.amazon.com/dp/1496353862

Medical Journal Articles:
From Google Scholar: https://scholar.google.com/citations?user=Q4kTU5YAAAAJ&hl=en
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