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JACS

Surgical Innovation and AI

This curated collection of articles explores the latest advancements in surgical technology. The articles highlighted here cover a wide range of topics, including robotic surgery, augmented reality, machine learning, and artificial intelligence. Scroll to the CME Articles section for opportunities to earn AMA PRA Category 1 Credits (TM) related to this collection.

Surgical Innovation and AI

Featured Articles

Robotics vs Laparoscopy in Foregut Surgery: Systematic Review and Meta-Analysis Analyzing Hiatal Hernia Repair and Heller Myotomy

Robotic surgery is increasingly common in foregut procedures. When compared with conventional laparoscopy, robotic hiatal hernia repair outcomes are non-inferior, while robotic Heller myotomy is associated with significantly fewer esophageal perforations and reinterventions.

In Search of the Truth: Choice of Ground-Truth for Predictive Modeling of Trauma Team Activation in Pediatric Trauma

Machine learning models may be used to improve accuracy and reliability of trauma team activation level prediction. To prioritize patient safety and best detect undertriage, the union of the Cribari and Need for Trauma Intervention criteria appears to be the best ground-truth for predicting pediatric trauma team activation level.

Outpatient and Ambulatory Extended Recovery Robotic Hepatectomy: Multinational Study of 307 Cases

Well-selected outpatient robotic hepatectomy is safe, including superior or posterior liver resection that is challenging with non-articulating laparoscopic instruments. Our data suggest that short-stay robotic-assisted liver resection is safe, oncologically sound, and benefits patients.

Articles

Validation of Artificial Intelligence-Based POTTER Calculator in Emergency General Surgery Patients Undergoing Laparotomy: Prospective, Bi-Institutional Study

Panossian, Vahe S; Argandykov, Dias; Arnold, Suzanne C; et al

Efficacy of Augmented Reality Combined with Indocyanine Green Fluorescence Imaging Guided Laparoscopic Segmentectomy for Hepatocellular Carcinoma

Wang, Dehui MM; Hu, Haoyu MD; Zhang, Yuwei MM; et al

Reflections on the US Withdrawal from Afghanistan: Insight into the Evolving Battlefield and the Need for Adaptive Responsiveness

Bozzay, Joseph D MD, FACS; Gurney, Jennifer M MD, FACS; Purcell, Richard L MD; et al

Real-Time Augmented Reality Annotation for Surgical Education during Laparoscopic Surgery: Results from a Single-Center Randomized Controlled Trial and Future Aspects

Huettl, Florentine MD; Heinrich, Florian PhD; Boedecker, Christian MD; et al

Perioperative and Disease-Free Survival Outcomes after Hepatectomy for Centrally Located Hepatocellular Carcinoma Guided by Augmented Reality and Indocyanine Green Fluorescence Imaging: A Single-Center Experience

Zhu, Wen MM; Zeng, Xiaojun MM; Hu, Haoyu MD; et al

Preliminary Exploration on the Efficacy of Augmented Reality-Guided Hepatectomy for Hepatolithiasis

Wu, Xiwen MM; Zeng, Ning MD; Hu, Haoyu MD; et al

Artificial Intelligence to Predict Quality of Life Outcomes for Vascular Interventions of the Leg

Brothers, Thomas E MD, FACS; Baliga, Prabhakar MD, FACS

Artificial Intelligence and Surgery: Ethical Dilemmas and Open Issues

Cobianchi, Lorenzo MD, PhD; Verde, Juan Manuel MD; Loftus, Tyler J MD; et al

Validation of Artificial Intelligence-Based POTTER Calculator in Emergency General Surgery Patients Undergoing Laparotomy: Prospective, Bi-Institutional Study

Panossian, Vahe S MD; Argandykov, Dias MD; Arnold, Suzanne C MD; et al

Open Retromuscular Lateral Abdominal Wall Hernia Repair: An Algorithmic Approach and Long-Term Outcomes at a Single Center

Montelione, Katherine C MD, MS; Petro, Clayton C MD; Krpata, David M MD, FACS; et al

Recipient Survival after Orthotopic Liver Transplantation: Interpretable Machine Learning Survival Tree Algorithm for Patient Specific Outcomes

Rogers, Michael P MD, MS; Janjua, Haroon M MS; Read, Meagan MD; et al

American College of Surgeons NSQIP Risk Calculator Accuracy Using a Machine Learning Algorithm Compared with Regression

Liu, Yaoming PhD; Ko, Clifford Y MD, MS, MSHS, FACS; Hall, Bruce L MD, PhD, MBA, FACS; Cohen, Mark E PhD

Machine Learning Models for Predicting the Outcomes of Surgical Treatment of Colorectal Liver Metastases

Moaven, Omeed MD; Tavolara, Thomas E PhD; Valenzuela, Cristian D MD; et al

Machine Learning Refinement of the NSQIP Risk Calculator: Who Survives the “Hail Mary” Case?

Rogers, Michael P MD, MS; Janjua, Haroon MS; DeSantis, Anthony J MD; et al

Machine Learning Approach to Stratifying Prognosis Relative to Tumor Burden after Resection of Colorectal Liver Metastases: An International Cohort Analysis

Paro, Alessandro MD; Hyer, Madison J MS; Tsilimigras, Diamantis I MD; et al

Novel Machine Learning Approach for the Prediction of Hernia Recurrence, Surgical Complication, and 30-Day Readmission after Abdominal Wall Reconstruction

Hassan, Abbas M MD; Lu, Sheng-Chieh PhD; Asaad, Malke MD; et al

Overtriage, Undertriage, and Value of Care after Major Surgery: An Automated, Explainable Deep Learning-Enabled Classification System

Loftus, Tyler J MD; Ruppert, Matthew M BS; Shickel, Benjamin PhD; et al

Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm

Zhu, Ying PhD; Simon, Gyorgy J. PhD; Wick, Elizabeth C. MD, FACS; et al

Artificial Intelligence Methods and Artificial Intelligence-Enabled Metrics for Surgical Education: A Multidisciplinary Consensus

Vedula, S Swaroop MBBS, MPH, PhD; Ghazi, Ahmed MD, FEBU, MHPE; Collins, Justin W MBChB, MD, FRCS; et al

Impact of Robotic Surgery Objective Performance Indicators: A Systematic Review

Gerull, William MD; Kulason, Sue PhD; Shields, Mallory C PhD; et al

Hidden Port Site Incision for Robotic Foregut and Hepatopancreatobiliary Operation: A Cosmetically Superior Approach

Fefferman, Marie L MD; Zheng, Caiwei MD; Varsanik, A Mary MD; Vigneswaran, Yalini MD, FACS

Simple Trocar Placement for Robotic Liver and Pancreatic Surgery: Multiple Access Devices at 5-cm Single Umbilicus Incision with 2 Robotic Ports

Kawaguchi, Yoshikuni MD, PhD, MPH, MMA; Ito, Kyoji MD, PhD; Abe, Satoru MD; et al

Robotic Enhanced-View Totally Extraperitoneal vs Intraperitoneal Onlay Mesh Evaluation: 1-Year Exploratory Outcomes of the REVEAL Randomized Clinical Trial

Petro, Clayton C MD, FACS; Maskal, Sara M MD; Renton, David B MD, FACS; et al

Outpatient and Ambulatory Extended Recovery Robotic Hepatectomy: Multinational Study of 307 Cases

Park, James O MD, FACS; Lafaro, Kelly MD, MPH; Hagendoorn, Jeroen MD; et al

Four-Day Robotic Whipple: Early Discharge after Robotic Pancreatoduodenectomy

Fong, Zhi Ven MD, MPH; Lwin, Thinzar M MD; Aliaj, Agim MBBS; et al

Analysis of Conflicts of Interest in Studies Related to Robotics in Gastrointestinal and Abdominal Wall Surgery

Jafar, Uzair MBBS; Usama, Muhammad MBBS; Hase, Niklas E BS; et al

CME Articles

March 2025

  • Validation of Artificial Intelligence-Based POTTER Calculator in Emergency General Surgery Patients Undergoing Laparotomy: Prospective, Bi-Institutional Study
Access JACS CME

Podcast Episode

Episode 32: Validation of Artificial Intelligence-Based POTTER Calculator in Emergency General Surgery Patients Undergoing Laparotomy: Prospective, Bi-Institutional Study      

In this episode, Tom Varghese, MD, FACS, is joined by Haytham Kaafarani, MD, MPH, FACS, and Vahe Panossian, MD, from the Department of Surgery, Massachusetts General Hospital and Harvard Medical School. They discuss the recent article by Drs Kaafarani and Panossian, “Validation of Artificial Intelligence-Based POTTER Calculator in Emergency General Surgery Patients Undergoing Laparotomy: Prospective, Bi-Institutional Study.” This study found that POTTER accurately predicts mortality and postoperative complication, and the superior accuracy, user-friendliness, and interpretability of POTTER make it a useful bedside tool for preoperative counseling. 

Featured Video

Dr Chacon discusses her recently published article in JACS, In Search of the Truth: Choice of Ground-Truth for Predictive Modeling of Trauma Team Activation in Pediatric Trauma.