July 21, 2022

Artificial Intelligence in Critical Care Medicine

CLICK HERE TO REGISTER!

Target Audience
Healthcare providers of all specialties may benefit from the information presented.

Description
This webinar will provide an introduction to artificial intelligence  in medicine, as well as detail artificial intelligence and clinical informatics in critical care. Dr. Lal will also discuss future steps and research opportunities in this area of medicine.   

Bio
Amos Lal is a Critical Care Medicine and Pulmonary physician at the Mayo Clinic, Rochester Minnesota, . His major clinical and research interests include Artificial intelligence in Critical Care, Clinical Informatics, infections in ICU, COVID-19 related research, Quality improvement and outcomes related research in Sepsis. Dr. Lal has published over 150 manuscripts in peer review journals internationally and has given presentations on his work at multiple international meetings and academic conferences. His diverse publication portfolio includes work in critical care/intensive care medicine and pulmonary diseases, infectious diseases and non-invasive cardiology. His other areas of interest include improvement in healthcare delivery in the underserved areas internationally by providing clinical care and teaching in developing countries such as Cambodia and Haiti. Dr. Lal is an elected Fellow of American College of Physicians, In-training Steering committee member for Society of Critical Care Medicine and a member of American College of Chest Physicians.

Learning Objectives
At the conclusion of this activity, the attendee should be able to:

  1. Have a broad overview of Artificial Intelligence (AI) in medicine
  2. Understand the currently available AI models in critical care
  3. Envisage the current Approach to developing clinically useful AI models
  4. Identify future direction and research opportunities

References

  1. Komorowski M, Celi LA, Badawi O, Gordon AC, Faisal AA. The Artificial Intelligence Clinician learns optimal treatment strategies for sepsis in intensive care. Nat Med. 2018 Nov;24(11):1716-1720. doi: 10.1038/s41591-018-0213-5. Epub 2018 Oct 22. PMID: 30349085.
  2. Lal A, Li G, Cubro E, Chalmers S, Li H, Herasevich V, Dong Y, Pickering BW, Kilickaya O, Gajic O. Development and Verification of a Digital Twin Patient Model to Predict Specific Treatment Response During the First 24 Hours of Sepsis. Crit Care Explor. 2020 Nov 16;2(11):e0249. doi: 10.1097/CCE.0000000000000249. PMID: 33225302; PMCID: PMC7671877.
  3. Lal A, Pinevich Y, Gajic O, Herasevich V, Pickering B. Artificial intelligence and computer simulation models in critical illness. World J Crit Care Med. 2020 Jun 5;9(2):13-19. doi: 10.5492/wjccm.v9.i2.13. PMID: 32577412; PMCID: PMC7298588.
  4. Eddy DM, Schlessinger L. Archimedes: a trial-validated model of diabetes. Diabetes Care. 2003 Nov;26(11):3093-101. doi: 10.2337/diacare.26.11.3093. PMID: 14578245.
  5. Dang J, Lal A, Flurin L, James A, Gajic O, Rabinstein AA. Predictive modeling in neurocritical care using causal artificial intelligence. World J Crit Care Med. 2021 Jul 9;10(4):112-119. doi: 10.5492/wjccm.v10.i4.112. PMID: 34316446; PMCID: PMC8291004.

Disclosure
Dr. Lal did not report any financial relationships or conflicts of interest. 

SMA Menu