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...
PURPOSE: To propose a computer-assisted method for distinguishing uterine sarcoma from leiomyomas based on perfusion weighted magnetic resonance imaging (PWI).
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...
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...
Nan fang yi ke da xue xue bao = Journal of Southern Medical University
Jan 20, 2026
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...
International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
Dec 1, 2025
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...
The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
May 1, 2024
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 ...
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