Machine Learning and Precision Medicine in Emergency Medicine: The Basics.
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As machine learning (ML) and precision medicine become more readily available and used in practice, emergency physicians must understand the potential advantages and limitations of the technology. This narrative review focuses on the key components of machine learning, artificial intelligence, and precision medicine in emergency medicine (EM). Based on the content expertise, we identified articles from EM literature. The authors provided a narrative summary of each piece of literature. Next, the authors provided an introduction of the concepts of ML, artificial intelligence as an extension of ML, and precision medicine. This was followed by concrete examples of their applications in practice and research. Subsequently, we shared our thoughts on how to consume the existing research in these subjects and conduct high-quality research for academic emergency medicine. We foresee that the EM community will continue to adapt machine learning, artificial intelligence, and precision medicine in research and practice. We described several key components using our expertise.
Published Version (Please cite this version)
Lee, Sangil, Samuel H Lam, Thiago Augusto Hernandes Rocha, Ross J Fleischman, Catherine A Staton, Richard Taylor and Alexander T Limkakeng (2021). Machine Learning and Precision Medicine in Emergency Medicine: The Basics. Cureus, 13(9). p. e17636. 10.7759/cureus.17636 Retrieved from https://hdl.handle.net/10161/24039.
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Dr. Alexander T. Limkakeng, Jr., MD, MHSc, FACEP is a Professor of Emergency Medicine, Vice Chair of Clinical Research, Director of the Acute Care Research Team, and Director of the Resident Research Fellowship for the Department of Emergency Medicine in the Duke University School of Medicine in Durham, North Carolina.
Dr. Limkakeng has served as chair of the American College of Emergency Physicians (ACEP) Research Committee, and been the Course Director of the ACEP Research Forum from 2016-2018, the largest emergency medical research platform in the nation. He is also the Assistant Director of ACEP’s Emergency Medicine Basic Research Skills course. He was elected to the Nominating Committee of the Society of Academic Emergency Medicine.
As a researcher, Dr. Limkakeng has led multiple clinical trials and interdepartmental sponsored projects and is author on over 100 peer-reviewed manuscripts. These include studies in emergency conditions such as COVID-19, traumatic brain injury, hypertension, heart failure, thrombosis, stroke, envenomations, and septic shock. His research has been funded by grants totaling over $5 million dollars. He has lectured internationally on acute coronary syndrome, responsible conduct of research, design of clinical trials, and precision medicine in emergency care. He has led Duke’s involvement in NIH-funded research networks and industry-funded work that led to FDA approval for multiple high-sensitivity cardiac troponin assays. He now serves as Co-PI for the Duke U24 Hub in the NIH Early Phase Pain Investigation Clinical Network (EPPIC-Net) (1U24NS114416) and a co-PI on the Duke U24 Hub award (1U24NS129498) in the NIH Strategies to Innovate Emergency Care Clinical Trials (SIREN) Network.
His personal research interest is finding new ways to diagnose acute coronary syndrome. In particular, he is interested in novel biomarkers and precision medicine approaches to this problem. The common element throughout this work is a focus on time-sensitive health conditions.
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