AIMC Topic: Leiomyoma

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Machine Learning to Differentiate T2-Weighted Hyperintense Uterine Leiomyomas from Uterine Sarcomas by Utilizing Multiparametric Magnetic Resonance Quantitative Imaging Features.

Academic radiology
RATIONALE AND OBJECTIVE: Uterine leiomyomas with high signal intensity on T2-weighted imaging (T2WI) can be difficult to distinguish from sarcomas. This study assessed the feasibility of using machine learning to differentiate uterine sarcomas from l...

Robot-assisted enucleation of large dumbbell-shaped esophageal schwannoma: a case report.

BMC surgery
BACKGROUND: Esophageal schwannomas are extremely rare, with few cases reported in the literature. Traditionally, resection of esophageal schwannoma is typically performed using thoracotomy or video-assisted thoracic surgery. However, large, irregular...

Flexible robotics in pelvic disease: does the catheter increase applicability of embolic therapy?

The Journal of cardiovascular surgery
Interventional radiology procedures, equipment, and techniques as well as image guidance have developed dramatically over the last few decades. The evidence for minimally invasive interventions in vascular and oncology fields is rapidly growing and s...

Comparison of Two Endovascular Steerable Robotic Catheters for Percutaneous Robot-Assisted Fibroid Embolization.

Cardiovascular and interventional radiology
PURPOSE: To compare outcomes of percutaneous robot-assisted uterine fibroid embolization (UFE) using two different endovascular robotic catheters.

A Technique for Vascular Control During Robotic-assisted Laparoscopic Myomectomy.

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To show and describe a unique method for improved vascular control when performing a robotic myomectomy.

[Enhancement of radiomics-based machine learning models for predicting efficacy of high-intensity focused ultrasound ablation of uterine fibroids using undersampling methods].

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
OBJECTIVES: To improve the accuracy of machine learning models for preoperative prediction of high-intensity focused ultrasound (HIFU) ablation efficacy for uterine fibroids by correcting class imbalance in small sample datasets using undersampling m...

Machine learning models for prediction of NPVR ≥80% with HIFU ablation for uterine fibroids.

International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
BACKGROUND: Currently high-intensity focused ultrasound (HIFU) is widely used to treat uterine fibroids (UFs). The aim of this study is to develop a machine learning model that can accurately predict the efficacy of HIFU ablation for UFs, assisting t...

Application of Computer-Assisted Endoscopic Ultrasonography Based on Texture Features in Differentiating Gastrointestinal Stromal Tumors from Benign Gastric Mesenchymal Tumors.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
BACKGROUND/AIMS:  Gastrointestinal stromal tumors are common gastric mesenchymal tumors that are potentially malignant. However, endoscopic ultrasonography is poor in diagnosing gastrointestinal stromal tumors. The study investigated the efficacy of ...