A multicenter analysis revealed that ChatGPT-4o effectively enhances patient education before and after surgery. Evaluating audio responses to frequently asked questions, the model achieved an average accuracy score of 4.12/5 and a relevance score of 4.46/5. Postoperative responses were notably more accurate and less harmful than preoperative ones. Results suggest that integrating ChatGPT-4o in clinical […]
Category: Digital Surgery and Telemedicine
Machine learning effectively predicts postpancreatectomy acute pancreatitis
A novel machine learning model successfully predicts postpancreatectomy acute pancreatitis (PPAP) in patients following pancreaticoduodenectomy. In a cohort of 381 patients, 88 (23.09%) developed PPAP, which was notably associated with a higher occurrence of postoperative pancreatic fistulas (55.68%). Various algorithms, including logistic regression and gradient boosting, were tested, with recursive feature elimination optimizing variable selection. […]
Improved visualization of surgical needle tips enhances accuracy
A novel model was developed to visualize hidden surgical needle tips within organs, addressing challenges in laparoscopic procedures that could lead to complications like anastomotic leakage. Testing revealed real-time image inference at 33.4 frames per second and a mean needle misalignment of just 1.03 mm, well below the 1.8 mm threshold. These findings suggest that […]
AI has transformative potential for surgical education.
Artificial intelligence could revolutionize surgical education by providing personalized feedback, improved competency evaluations, and enhanced candidate selection. AI-driven simulations foster adaptive learning among trainees, while intraoperative tools may assist surgeons in complex procedures. However, challenges such as data quality, ethical concerns, and the risk of overskilling need to be addressed. Developing regulatory frameworks emphasizing transparency […]
Machine learning accurately predicts temporary stoma formation in CD patients
A machine learning model effectively predicts temporary stoma formation following intestinal resection in Crohn’s disease patients. An analysis of 252 patient records identified eight key predictors, achieving an area under the curve (AUC) between 0.886 and 0.998. The random forest algorithm showed the highest predictive accuracy, leading to potential improvements in surgical decision-making and personalized […]
Intraoperative surgeon metrics predict robotic herniorrhaphy outcomes
Machine learning analysis on robotic ventral hernia repair data revealed that intraoperative surgeon performance indicators significantly influence postoperative complications. Evaluating 520 patients, the study achieved high predictive accuracy (0.95) for complications using various algorithms. Notably, 6.3% experienced complications at discharge, emphasizing the interplay between surgical techniques and patient-specific factors. The findings pave the way for […]
Machine learning model effectively predicts postoperative recurrence in duodenal adenocarcinoma
A machine learning-based model has been developed to predict postoperative recurrence in patients with duodenal adenocarcinoma, utilizing data from 1,830 patients who underwent radical surgery. Among 100 predictive models tested, the penalized regression + accelerated oblique random survival forest model (pam) delivered the highest performance with a concordance index (c-index) of 0.882 in the training […]
Deep learning model enhances safety in laparoscopic gastrectomy
A deep learning-based model was developed for real-time recognition of perigastric blood vessels during laparoscopic radical gastrectomy. In testing, the model demonstrated high precision (mean 0.9442) and recall (mean 0.9099) for arteries and maintained robust performance across various challenging conditions. It showed potential to improve intraoperative safety and reduce the risk of accidental bleeding, particularly […]
Machine learning predicts early recurrence risk in cholangiocarcinoma
A novel machine learning model effectively predicts very early recurrence (VER) of perihilar cholangiocarcinoma (PCCA) post-surgery. In a study of 434 patients, 15% experienced VER, significantly reducing median overall survival to 8.4 months compared to 38.5 months for those without recurrence (p
Ethical integration of AI is essential in academic surgery.
The incorporation of generative artificial intelligence in academic surgery presents transformative opportunities but also significant ethical challenges. Key benefits include improved efficiency in tasks like manuscript writing and clinical documentation. However, concerns regarding bias, transparency, intellectual property, and privacy necessitate strict guidelines for responsible use. The paper emphasizes the importance of ethical training and governance […]