AIMC Topic: Colectomy

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Establishment of a machine learning-based predictive model with dual-center external validation: investigating the role of robotic surgery in preventing delayed gastric emptying for right-sided colon cancer.

Journal of robotic surgery
After colorectal surgery, delayed gastric emptying (DGE) is a clinically significant postoperative complication that significantly lowers patients' quality of life. The evolving application of robotic surgery in gastrointestinal oncology continues to...

Deep learning neural network prediction of postoperative complications in patients undergoing laparoscopic right hemicolectomy with or without CME and CVL for colon cancer: insights from SICE (Società Italiana di Chirurgia Endoscopica) CoDIG data.

Techniques in coloproctology
BACKGROUND: Postoperative complications in colorectal surgery can significantly impact patient outcomes and healthcare costs. Accurate prediction of these complications enables targeted perioperative management, improving patient safety and optimizin...

Artificial intelligence-enhanced video-based assessment of surgical quality for training in laparoscopic right hemicolectomy: The "Marginal Gains" pilot study.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: The study aims to propose a standardised workflow with critical views for surgical quality assessment (SQA) in laparoscopic right hemicolectomy (LRH), to disseminate it through a "Marginal Gains" course, and to evaluate its impact throu...

A novel artificial intelligence framework to quantify the impact of clinical compared with nonclinical influences on postoperative length of stay.

Surgery
BACKGROUND: The relative proportion of clinical compared with nonclinical influences on length of stay after colectomy has never been measured. We developed a novel machine-learning framework that quantifies the proportion of length of stay after col...

Bowel preparation before elective right colectomy: Multitreatment machine-learning analysis on 2,617 patients.

Surgery
BACKGROUND: In the worldwide, real-life setting, some candidates for right colectomy still receive no bowel preparation, some receive oral antibiotics alone, some receive mechanical bowel preparation alone, and some receive mechanical bowel preparati...

Automated surgical skill assessment in colorectal surgery using a deep learning-based surgical phase recognition model.

Surgical endoscopy
BACKGROUND: There is an increasing demand for automated surgical skill assessment to solve issues such as subjectivity and bias that accompany manual assessments. This study aimed to verify the feasibility of assessing surgical skills using a surgica...

An artificial intelligence-designed predictive calculator of conversion from minimally invasive to open colectomy in colon cancer.

Updates in surgery
Minimally invasive surgery is safe and effective in colorectal cancer. Conversion to open surgery may be associated with adverse effects on treatment outcomes. This study aimed to assess risk factors of conversion from minimally invasive to open cole...

Real-time detection of active bleeding in laparoscopic colectomy using artificial intelligence.

Surgical endoscopy
BACKGROUND: Most intraoperative adverse events (iAEs) result from surgeons' errors, and bleeding is the majority of iAEs. Recognizing active bleeding timely is important to ensure safe surgery, and artificial intelligence (AI) has great potential for...

Proposal of set-up standardization for general surgery procedures with the CMR Versius system, a new robotic platform: our initial experience.

Langenbeck's archives of surgery
BACKGROUND: The article describes our initial experience using CMR Versius platform for several procedures in general surgery.