AIMC Topic: Hysterectomy

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Comparison of clinical hysterectomy indications with ai-based recommendations: a prospective study.

Scientific reports
This prospective study evaluated ChatGPT-4 as a decision-support tool by comparing its treatment recommendations with clinical decisions for 87 women (aged 40-65 years) scheduled for hysterectomy. Demographic, clinical, and ultrasonographic data were...

Hysterectomy as a predictor of depression: A comprehensive analysis using logistic regression and machine learning.

Journal of affective disorders
BACKGROUND: An increasing number of studies have shown that there is an inseparable connection between hysterectomy and occurrence of depression, and the impact on patient's mental health cannot be ignored. Therefore, this study utilized the National...

Predicting Robotic Hysterectomy Incision Time: Optimizing Surgical Scheduling with Machine Learning.

JSLS : Journal of the Society of Laparoendoscopic Surgeons
BACKGROUND AND OBJECTIVES: Operating rooms (ORs) are critical for hospital revenue and cost management, with utilization efficiency directly affecting financial outcomes. Traditional surgical scheduling often results in suboptimal OR use. We aim to b...

Machine Learning for the Prediction of Surgical Morbidity in Placenta Accreta Spectrum.

American journal of perinatology
OBJECTIVE:  We sought to create a machine learning (ML) model to identify variables that would aid in the prediction of surgical morbidity in cases of placenta accreta spectrum (PAS).

Distinguishing the Uterine Artery, the Ureter, and Nerves in Laparoscopic Surgical Images Using Ensembles of Binary Semantic Segmentation Networks.

Sensors (Basel, Switzerland)
Performing a minimally invasive surgery comes with a significant advantage regarding rehabilitating the patient after the operation. But it also causes difficulties, mainly for the surgeon or expert who performs the surgical intervention, since only ...

Machine learning models for prediction of postoperative venous thromboembolism in gynecological malignant tumor patients.

The journal of obstetrics and gynaecology research
AIM: To identify risk factors that associated with the occurrence of venous thromboembolism (VTE) within 30 days after hysterectomy among gynecological malignant tumor patients, and to explore the value of machine learning (ML) models in VTE occurren...

Introducing surgical intelligence in gynecology: Automated identification of key steps in hysterectomy.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: The analysis of surgical videos using artificial intelligence holds great promise for the future of surgery by facilitating the development of surgical best practices, identifying key pitfalls, enhancing situational awareness, and dissemin...

Gasless transvaginal natural orifice transluminal endoscopic surgery for hysterectomy and salpingectomy on a robot platform with flexible devices in a porcine model.

Scientific reports
In this report, we described a new technique of gasless V-NOTES for hysterectomy and salpingectomy on a robotic platform with flexible devices in a porcine model. As a result, the gynecological procedures were successfully completed. The total operat...

Validate robot-assisted total laparoscopic hysterectomy with four equally-spaced ports without an assistant port.

Journal of robotic surgery
To evaluate the usefulness of robot-assisted total laparoscopic hysterectomy with four equally-spaced ports (RA-TLH/4e) without an assistant port. In RA-TLH/4e, four da Vinci ports were placed horizontally at a height of 4 cm above the umbilicus with...

Gynecologic Surgical Subspecialty Training Decreases Surgical Complications in Benign Minimally Invasive Hysterectomy.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To evaluate the impact of gynecologic subspecialty training on surgical outcomes in benign minimally invasive hysterectomies (MIHs) while accounting for surgeon volume.