Join the Hernia Team from Carolinas Medical Center as they discuss applications of artificial intelligence in predicting outcomes for patients undergoing abdominal wall reconstruction. Emerging technologies are allowing us to understand hernia patients who are at risk for increased surgical complexity and postoperative complications – find out more in this Journal Review episode.

Hosts:

Dr. Sullivan “Sully” Ayuso, Chief Resident, Carolinas Medical Center, @SAyusoMD 
 Dr. Todd Heniford, Chief of GI & MIS, Carolinas Medical Center, @THeniford 
 Dr. Vedra Augenstein, Professor of Surgery, Carolinas Medical Center, @VedraAugenstein 
Dr. Monica Polcz, Attending Surgeon, Baptist Health (FL) 

Learning Objectives:

Provide and introduction to artificial intelligence
Develop an understanding of the applications of artificial intelligence in surgical outcome prediction for patients undergoing hernia repair
Learn how risk stratification of hernia patients can affect their care

References:
Elhage et al, Development and Validation of Image-Based Deep Learning Models to Predict Surgical Complexity and Complications in Abdominal Wall Reconstruction, JAMA Surgery, 2021

https://pubmed.ncbi.nlm.nih.gov/34232255/



Ayuso et al, Predicting Rare Outcomes in Abdominal Wall Reconstruction Using Image-Based Deep Learning Models, Surgery, 2023 

https://pubmed.ncbi.nlm.nih.gov/36229252/ 



Hassan et al, Novel Machine Learning Approach for Prediction of Hernia Recurrence, Surgical Complication, and 30-Day Readmission after Abdominal Wall Reconstruction, JACS, 2022

https://pubmed.ncbi.nlm.nih.gov/35426406/

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