AIMC Topic: Laparoscopy

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Machine learning-based risk modeling for safety-focused learning curve assessment in robotic left-sided colorectal cancer surgery.

Journal of robotic surgery
The transition from laparoscopic to robotic surgery for left-sided colorectal cancer raises safety concerns during the learning curve, particularly when complex cases are preferentially selected for the robotic platform. We evaluated a machine learni...

A visual exploration of the evolutionary trajectory in robotic surgery for gastrointestinal malignancies.

Journal of robotic surgery
Robotic surgery has emerged as a key minimally invasive approach for gastrointestinal malignancies, stimulating substantial global research activity. This study employed bibliometric and visual methods to map the knowledge structure, evolutionary tra...

Developing and external validating a prediction model using machine learning and logistic regression: informing the surgical approach for robotic surgery based on preoperative MRI.

Journal of robotic surgery
BACKGROUND: Preoperative prediction of surgical difficulty in robotic-assisted total mesorectal excision for rectal cancer remains challenging. While pelvic anatomical parameters measured by MRI have been associated with surgical complexity in laparo...

Localized Muscular Fatigue in Robotic-Assisted Laparoscopic Surgery: Predictive Modeling Study.

JMIR formative research
BACKGROUND: Robotic-assisted surgery (RAS) has grown rapidly in recent decades, and several RAS procedures have become the standard. However, the physical and mental demands of minimally invasive surgery (MIS) techniques can lead to ergonomic shortco...

Research hotspots and trends of robotic rectal cancer surgery: a bibliometric analysis (2006-2025).

Journal of robotic surgery
Rectal cancer presents complex surgical challenges due to the confined pelvic anatomy. Robotic-assisted surgery has gained prominence for its enhanced precision, dexterity, and ergonomics compared to conventional laparoscopy. This bibliometric analys...

Machine learning combined with body composition predicts surgical difficulty in mid-low rectal cancer surgery.

Annals of medicine
BACKGROUND: This study sought to identify critical body composition characteristics associated with surgical difficulty in Laparoscopic Total Mesorectal Excision (LaTME) and to develop and validate an interpretable machine learning model using body c...

Deep learning-based vessel and nerve recognition model for lateral lymph node dissection: a retrospective feasibility study.

Langenbeck's archives of surgery
PURPOSE: Lateral lymph node dissection for rectal cancer is challenging because of the presence of blood vessels and nerves essential for postoperative genitourinary function and leg movements. Identifying these structures during surgery is crucial. ...

Explainable prediction of hypothermia risk in laparoscopic surgery: a retrospective cross-sectional study using machine learning.

BMC surgery
OBJECTIVE: This study aims to develop multiple machine learning models for predicting hypothermia risk in laparoscopic surgery and to perform interpretability analysis of the best-performing model. Our goal is to provide robust decision support for c...

Robotic adrenalectomy: a comprehensive review of perioperative outcomes, comparative efficacy, and technological advancements.

Journal of robotic surgery
The adrenal glands are small but vital endocrine organs responsible for hormone production, which is essential for stress response, fluid balance, and blood pressure regulation. Adrenalectomy, the surgical removal of one or both adrenal glands, is in...

Mapping the knowledge landscape of robotic colorectal cancer surgery: a visualization study.

Journal of robotic surgery
Robotic surgery has now been widely applied in the treatment of colorectal cancer (CRC), driving significant growth in related research activities. This study aims to reveal the research hotspots, emerging frontiers, and future research trends in the...