To advance solid organ transplantation, the integration of personalized medicine is paramount. Beyond enhanced risk assessment and diagnostics, there’s a pressing need for targeted therapies and predictive markers. The study advocates a paradigm shift, urging clinicians to embrace uncertainty and probabilistic reasoning. Crucially, effective communication about inherent uncertainties is vital for both healthcare professionals and […]
Category: Digital Surgery and Telemedicine
Navigating Robotic Surgery Skill Assessment: A Systematic Review
In the ever-evolving realm of robotic surgery, researchers conducted a systematic review to pinpoint reliable tools for assessing surgeons’ technical skills. Among 247 studies, global rating scales and the da Vinci Skills Simulator took the lead. However, scrutiny revealed a lack of robust validation for both manual and automated assessment tools. The verdict: before entering […]
Predicting Pancreatic Complications: Machine Learning Triumphs Over Traditional Models.
Researchers crafted an innovative machine learning (ML) model for forecasting clinically relevant postoperative pancreatic fistula (CR-POPF) after pancreaticoduodenectomy. The ML model consistently outshone the existing modified fistula risk score (MFRS) in both internal and external validations, proving its versatility and efficacy in enhancing CR-POPF prediction. This breakthrough offers a more accurate risk stratification tool, potentially […]
Innovative AI Support in Surgery for Laparoscopic Cholecystectomy: Early Clinical Trial Shows Promise.
Surgeons embrace real-time artificial intelligence (AI) assistance for laparoscopic cholecystectomy, overcoming technical and cultural hurdles. The study proves the feasibility of deploying multiple AI models concurrently in operating rooms, offering live assistance during procedures. The research delves into diverse clinical applications, involving a collaborative effort with key stakeholders across disciplines. This marks a significant stride […]
Robotic Surgery Revolution: 3D Drawing Annotations Enhance Telementoring
In a groundbreaking study, researchers explored the effectiveness of telementoring in robotic surgery with 3D drawing annotations. Conducted 140 km apart, the study used the Saroa™ surgical robot, evaluating 20 medical students. The 3D annotation group demonstrated potential for shorter working time, fewer retries, and needle drops compared to the control. Notably, they outperformed in […]
Big Data Shapes Future of Hepatopancreatobiliary Cancer Surgery
In the realm of surgical oncology, randomized controlled trials (RCTs) often face recruitment and standardization challenges. This study dives into hepatopancreatobiliary (HPB) cancer surgery, spotlighting the pivotal role of large databases. While RCTs provide crucial evidence, big data steps in where they fall short. Beyond justifying current practices, this research maps the future of HPB […]
Setting the Bar for Surgical Video Deidentification Standards
This article dives into the crucial realm of standards for deidentifying surgical videos. In the modern operating room, surgical videos offer a wealth of valuable data. They enable performance assessment and complication rate analysis, enhancing the future of surgical care. The integration of routine video capture and analysis presents exciting prospects for quality improvement, competency […]
General Surgery Residents’ Views on the Role of Artificial Intelligence in Medicine
General surgery residents’ perspectives on artificial intelligence (AI) in medicine were explored through a survey. Among 31 participants, AI’s top applications were identified, with 24% favoring diagnostics and 12% supporting its role in identifying anatomical structures during surgeries. Residents expressed excitement about AI for repetitive tasks (70.97%) and believed it could enhance medical knowledge (67.74%). […]
Immediate Release of Electronic Health Information: Clinician and Patient Perceptions
The 21st Century Cures Act mandates the immediate release of electronic health information (EHI) to patients. Researchers surveyed 33 clinicians and 30 patients, conducting interviews with a subset of 8 clinicians and 12 patients to explore their perceptions of this immediate EHI release. Ten themes emerged, revealing differences in how clinicians and patients perceive patient […]
Machine Learning Model Predicts Benign Anastomotic Strictures in Rectal Cancer Patients
Aiming to improve the prediction of benign anastomotic strictures (BAS) in patients who’ve undergone rectal cancer surgery, a study harnessed machine learning. Data from 1,973 patients were analyzed using multiple machine learning models, with the random forest (RF) model emerging as the best predictor of BAS. The RF model achieved an impressive area under the […]