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JACS

Surgical Innovation and AI

surgical-robot.jpg

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™ related to this collection. 

Featured Articles

Enhancing Accuracy of Operative Reports with Automated Artificial Intelligence Analysis of Surgical Video

Surgical operative reports are tedious to create, are inherently subjective, and may contain inaccuracies. We explored automated creation of video-based AI surgical operative reports in robotic-assisted radical prostatectomy. Operative reports written by AI had higher overall accuracy than those written by surgeons.

Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database

In the largest pediatric surgical infection prediction study, we built machine learning models and recommend a regularized logistic regression model for clinical integration, balancing performance and feasibility for implementation. Findings support using routine preoperative data for personalized infection prevention and preoperative planning.

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

This study prospectively validates the POTTER AI risk calculator in emergency laparotomy patients. POTTER accurately predicts mortality (c-statistic: 0.90) and postoperative complications (c-statistics: 0.80-0.89). The superior accuracy, user-friendliness, and interpretability of POTTER make it a useful bedside tool for preoperative counseling.

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

NIH Funding for Artificial Intelligence in Surgical Specialties: Allocation and Alignment with US Disease Burden

Rahul Gorijavolu, Andrew Cho, Saurav Boparai, et al

Development of a Predictive Calculator for the Need for Abdominoperineal Resection after Chemoradiation Therapy in Anal Squamous Cell Carcinoma

Wignakumar, Anjelli MBBS, BSc (Hons); Emile, Sameh H MBBCh, MSc, MD, FACS; Barnes, Spencer BS, et al

Artificial Intelligence Simplification of English and Spanish Surgical Consent Forms: 1-Size Does Not Fit All

Pettigrew, Morgan F MD; Nunez-Rocha, Ricardo E MD; Govindu, Sai R BS; et al

Governance Framework for Safe and Ethical Implementation of Artificial Intelligence in Surgery: A Modified-Delphi Consensus

Hassan, Abbas M MD, PhD1; Coert, J Henk MD, PhD2; Clemens, Mark W MD, FACS, MBA, FACHE, et al

Predictive Model for Mild Autonomous Cortisol Secretion in Patients Evaluated in Artificial Intelligence-Driven Adrenal Incidentaloma Clinic

Kostek, Mehmet MD, FACS; McLeod, Chandler PhD; Kasmirski, Julia MD, et al

Goals of Care Transitions following Postoperative Undertriage

Loftus, Tyler J MD, PhD, FACS; Ruppert, Matthew M BS; Hu, Die, et al

Long-Term Follow-Up in Liver Transplantation and Combined Cardiac Surgery: Validation and Refinement of the LT+CS Risk Score Using Advanced Machine Learning

Oliveira, Laura B MD; Wehrle, Chase J MD; Wehbe, Sarah MD; et al

Toward Opioid-Free Ambulatory Surgery: A Prospective Study Using Machine Learning to Predict Postoperative Opioid Use

Renshaw, Savannah MPH, MPA; Satija, Divyaam MD; Aly, Abdullah MD, et al

Death of the Personal Statement: Qualitative Comparison Between Human-Authored and Artificial Intelligence–Generated Medical School Admissions Essays

Vaccaro, Matthew J BS; Sharma, Ishpriya PhD; Espina-Rey, Andrea P MPH, CPH; et al

Near-Infrared Autofluorescence Signature: A New Parameter for Intraoperative Assessment of Parathyroid Glands in Primary Hyperparathyroidism

Akgun, Ege MD; Ibrahimli, Arturan MD; Berber, Eren, et al

Improved American College of Surgeons NSQIP Hospital Benchmarking with Risk Adjustment for Many CPT Codes Rather Than Just the Principal Code

Cohen, Mark E PhD; Liu, Yaoming PhD; Hall, Bruce L, et al

Data Extraction and Curation from Radiology Reports for Pancreatic Cyst Surveillance Using Large Language Models

Choubey, Ankur P MD, MPH; Eguia, Emanuel MD, MS; Hollingsworth, Alexander MS, et al

The Digital Standardized Patient: An Artificial Intelligence Coach for Cultural Dexterity in Surgical Care

Rao, Arya S BA; Lee, Richard S BS; Bott, Ethan BS; et al

Clinical Validation of Computer-Aided Diagnosis Software for Preventing Retained Surgical Sponges

Kurisaki, Ken MD; Soyama, Akihiko MD, PhD, FACS; Hamauzu, Shin ME; et al

National Multi-Institutional Validation of a Surgical Transfusion Risk Prediction Model

Lou, Sunny S MD, PhD; Liu, Yaoming PhD; Cohen, Mark E, et al

Deep Neural Network for the Prediction of KRAS Genotype in Rectal Cancer

Ghareeb, Waleed M MD, PhD; Draz, Eman MD; Madbouly, Khaled, et al

Video-Based Assessment and Prediction of Surgical Outcomes in Sleeve Gastrectomy

Ballo, Mattia MD; Profant, Craig MD; Tindal, Elizabeth W MD, MPH, et al

Machine Learning Prediction of Financial Toxicity in Patients with Resected Lung Cancer

Deboever, Nathaniel; Al-Tashi, Qasem; Eisenberg, Michael; et al

Leveraging Artificial Intelligence as a Safety Net for Incidentally Identified Lung Nodules at a Tertiary Center

Woodhouse, Palina; Paez, Rafael; Meyers, Patrick; 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

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

July 2026

  • Governance framework for safe and ethical implementation of artificial intelligence in surgery: a modified-delphi consensus
  • Improving trauma triage accuracy with large language models: a comparison to human expert decisions 
  • Artificial intelligence simplification of English and Spanish surgical consent forms: 1-size does not fit all 

May 2026

  • Predictive model for mild autonomous cortisol secretion in patients evaluated in artificial intelligence-driven adrenal incidentaloma clinic 

March 2026

  • Development of a predictive calculator for the need for abdominoperineal resection after chemoradiation therapy in anal squamous cell carcinoma 

March 2025

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

Podcast Episodes

Episode 46: Artificial Intelligence Simplification of English and Spanish Surgical Consent Forms: 1-Size Does Not Fit All

In this episode, Lillian Erdahl, MD, FACS, is joined by Morgan Pettigrew, MD, from UT Southwestern. They discuss Dr Pettigrew’s recent article, “Artificial Intelligence Simplification of English and Spanish Surgical Consent Forms: 1-Size Does Not Fit All,” which found that while ChatGPT-4.0 improved the readability of English surgical consent forms, it did not improve readability of Spanish forms. To address this disparity, the authors developed a custom-trained GPT that improved readability of English and Spanish consent forms.

Episode 43: Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database

In this episode, Thomas K Varghese, Jr, MD, FACS, is joined by Carrie Chan, MSN, MPH, from the University of California, San Francisco, and Karthik Balakrishnan, MD, FACS, from Stanford Medicine Children’s Health. They discuss their recent article, “Development, Validation, and Comparison of Machine Learning Models for Predicting Pediatric Surgical Site Infections Using the NSQIP-P Database,” which represents the largest study to date on predicting pediatric surgical site infection. The authors developed machine-learning models and ultimately recommend a regularized logistic regression model for clinical integration, balancing performance and feasibility for implementation. Findings support using routine preoperative data for personalized infection prevention and preoperative planning.

Episode 40: From Surgeon Well-Being to Artificial Intelligence: 2025 Highlights

In this episode, JACS Editor-in-Chief Tom Varghese, MD, FACS, and Digital Media Editor Lillian Erdahl, MD, FACS, review 6 impactful articles from the past year, highlighting key themes shaping modern surgical practice. Dr Erdahl focuses on the surgeon as a subject, discussing research on moral distress, second-victim syndrome, health policy challenges, and peer surgical coaching. Dr Varghese then explores advances in surgical science, including pragmatic applications of artificial intelligence for risk prediction and operative documentation, as well as comparative evidence on robotic, laparoscopic, and open operation. Together, they emphasize clinically relevant research, thoughtful innovation, and ongoing critical inquiry to support surgeons and improve patient care. 

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.