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- 2016
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Mark
Morcellation and risk of malignancy in presumed ovarian fibromas/fibrothecomas
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- Contribution to journal › Debate/Note/Editorial
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Mark
Age-related differences in the sonographic characteristics of endometriomas
(
- Contribution to journal › Article
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Mark
Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis (IOTA) group.
(
- Contribution to journal › Article
- 2014
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Mark
Evaluating the risk of ovarian cancer before surgery using the ADNEX model to differentiate between benign, borderline, early and advanced stage invasive, and secondary metastatic tumours: prospective multicentre diagnostic study.
(
- Contribution to journal › Article
- 2013
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Mark
The risk of malignancy in unilocular cysts: a study on 1148 adnexal masses classified as unilocular cysts at transvaginal scan with review of the literature.
(
- Contribution to journal › Article
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Mark
Early-stage cervical cancer: Tumor delineation by magnetic resonance imaging and ultrasound - A European multicenter trial
(
- Contribution to journal › Article
- 2012
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Mark
External Validation of Diagnostic Models to Estimate the Risk of Malignancy in Adnexal Masses
(
- Contribution to journal › Article
- 2011
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Mark
A Novel Approach to Predict the Likelihood of Specific Ovarian Tumor Pathology Based on Serum CA-125: A Multicenter Observational Study.
2011) In Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 20. p.2420-2428(
- Contribution to journal › Article
- 2010
-
Mark
Sonographic characteristics of squamous cell cancer and adenocarcinoma of the uterine cervix.
2010) In Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Apr 8. p.512-516(
- Contribution to journal › Article
-
Mark
Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models
(
- Contribution to journal › Article