A comparative analysis of large language models versus traditional information extraction methods for real-world evidence of patient symptomatology in acute and post-acute sequelae of SARS-CoV-2.

Abstract

Authors

• Vedansh Thakkar
  Department of Surgery, University of Minnesota, Minneapolis, Minnesota, United States of America.
• Greg M Silverman
• Abhinab Kc
  University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
• Nicholas E Ingraham
  Division of Pulmonary and Critical Care, Department of Medicine, University of Minnesota Medical School, Minneapolis, Minnesota, United States of America.
• Emma K Jones
  Department of Surgery, University of Minnesota, Minneapolis, MN.
• Samantha King
  Department of Surgery, University of Washington, Seattle, Washington, United States of America.
• Genevieve B Melton
  Institute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, USA.
• Rui Zhang
  Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
• Christopher J Tignanelli
  From the Department of Surgery (C.J.T., G.B., G.B.M.), University of Minnesota, Minneapolis, Minnesota; Institute for Health Informatics (C.J.T., G.M.S., R.F., R.M., B.C.K., S.P., E.A.L., G.B.M.), University of Minnesota, Minneapolis, Minnesota; Department of Surgery (C.J.T., J.L.G.), North Memorial Health Hospital, Robbinsdale, Minnesota; North Memorial Health Hospital Emergency Medical Services (A.L.T.), Robbinsdale, Minnesota; and Department of Emergency Medicine (J.W.L.), North Memorial Health Hospital Emergency Medical Services, Robbinsdale, Minnesota.

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External Resources