MRI‐Based Machine Learning for Differentiating Borderline From Malignant Epithelial Ovarian Tumors: A Multicenter Study

Utility of DWI with quantitative ADC values in ovarian tumors: a meta-analysis of diagnostic test performance

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Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists

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A New Approach to Predict Progression-free Survival in Stage IV EGFR-mutant NSCLC Patients with EGFR-TKI Therapy

(2018) Jiangdian Song et al.   CLINICAL CANCER RESEARCH

MRI features and score for differentiating borderline from malignant epithelial ovarian tumors

(2018) Yong Ai Li et al.   EUROPEAN JOURNAL OF RADIOLOGY

Risk of borderline ovarian tumors among women with benign ovarian tumors: A cohort study

(2018) Sonia Guleria et al.   GYNECOLOGIC ONCOLOGY

Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values

(2018) David Bonekamp et al.   RADIOLOGY

Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer

(2018) Xiaochun Meng et al.   EUROPEAN RADIOLOGY

Clinicopathologic Features and Risk Factors for Recurrence of Mucinous Borderline Ovarian Tumors: A Retrospective Study With Follow-up of More Than 10 Years

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Role of proton MR spectroscopy in the differentiation of borderline from malignant epithelial ovarian tumors: A preliminary study

(2018) Feng Hua Ma et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Diagnostic value of whole body diffusion-weighted MRI compared to computed tomography for pre-operative assessment of patients suspected for ovarian cancer

(2017) Katrijn Michielsen et al.   EUROPEAN JOURNAL OF CANCER

An update on the role of PET/CT and PET/MRI in ovarian cancer

(2017) Benjapa Khiewvan et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

Multiparametric MRI for differentiation of borderline ovarian tumors from stage I malignant epithelial ovarian tumors using multivariate logistic regression analysis

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Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer

(2017) Jing Wang et al.   EUROPEAN RADIOLOGY

Diffusion kurtosis imaging for differentiating borderline from malignant epithelial ovarian tumors: A correlation with Ki-67 expression

(2017) Hai Ming Li et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Role of Imaging Tools for the Diagnosis of Borderline Ovarian Tumors: A Systematic Review and Meta-Analysis

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Imaging in gynecological disease (12): clinical and ultrasound features of invasive and non-invasive malignant serous ovarian tumors

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Fertility-sparing surgery for early stage epithelial ovarian cancer

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Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer

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Ovarian Cancer, Version 1.2016, NCCN Clinical Practice Guidelines in Oncology

(2016) Robert J. Morgan et al.   Journal of the National Comprehensive Cancer Network

MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays

(2016) Hui Li et al.   RADIOLOGY

Ovarian borderline tumors in the 2014 WHO classification: evolving concepts and diagnostic criteria

(2016) Steffen Hauptmann et al.   VIRCHOWS ARCHIV

Accuracy of intraoperative frozen section for the evaluation of ovarian neoplasms: an institutional experience

(2016) Atif Ali Hashmi et al.   World Journal of Surgical Oncology

Adnexal Masses: Role of Supplemental Imaging With Magnetic Resonance Imaging

(2015) Mahesh K. Shetty   SEMINARS IN ULTRASOUND CT AND MRI

Diffusion-weighted MR imaging for differentiating borderline from malignant epithelial tumours of the ovary: pathological correlation

(2014) Shu Hui Zhao et al.   EUROPEAN RADIOLOGY

Ovarian cancer

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Unilocular adnexal cysts with papillary projections but no other solid components: is there a diagnostic method that can classify them reliably as benign or malignant before surgery?

(2012) L. Valentin et al.   ULTRASOUND IN OBSTETRICS & GYNECOLOGY

Newly diagnosed and relapsed epithelial ovarian carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up

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