日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

O-RADS US Version 2022 Improves Patient Risk Stratification When Compared with O-RADS US Version 2019

与 O-RADS US 2019 版相比,O-RADS US 2022 版提高了患者风险分层能力。

Yoeli-Bik, Roni; Abramowicz, Jacques S; Wroblewski, Kristen; Donle, Leonhard; Longman, Ryan E; Lengyel, Ernst

Hybrid artificial intelligence echogenic components-based diagnosis of adnexal masses on ultrasound

基于混合人工智能回声成分的超声附件肿块诊断

Yoeli-Bik, Roni; Whitney, Heather M; Li, Hui; Bilecz, Agnes; Abramowicz, Jacques S; Lan, Li; Longman, Ryan E; Giger, Maryellen L; Lengyel, Ernst

The Ultrasonography Characteristics of Borderline Ovarian Tumor Subtypes

交界性卵巢肿瘤亚型的超声特征

Yoeli-Bik, Roni; Lengyel, Ernst; Timor-Tritsch, Ilan E; Kurnit, Katherine; Puiu, Serghei; Longman, Ryan E; Abramowicz, Jacques S

Molecular changes driving low-grade serous ovarian cancer and implications for treatment

驱动低级别浆液性卵巢癌的分子变化及其对治疗的影响

Kelliher, Lucy; Yoeli-Bik, Roni; Schweizer, Lisa; Lengyel, Ernst

AI-based automated segmentation for ovarian/adnexal masses and their internal components on ultrasound imaging

基于人工智能的卵巢/附件肿块及其内部成分超声图像自动分割

Whitney, Heather M; Yoeli-Bik, Roni; Abramowicz, Jacques S; Lan, Li; Li, Hui; Longman, Ryan E; Lengyel, Ernst; Giger, Maryellen L

Diagnostic Performance of Ultrasonography-Based Risk Models in Differentiating Between Benign and Malignant Ovarian Tumors in a US Cohort

美国人群中基于超声的风险模型在区分良性和恶性卵巢肿瘤方面的诊断性能

Yoeli-Bik, Roni; Longman, Ryan E; Wroblewski, Kristen; Weigert, Melanie; Abramowicz, Jacques S; Lengyel, Ernst