Epstein, E.

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

Van Calster, B., Van Hoorde, K., Valentin, L., Testa, A. C., Fischerova, D., Van Holsbeke, C., Savelli, L., Franchi, D., Epstein, E., Kaijser, J., et al. (2014) · BMJ

Ovarian cancer diagnosis and treatmentBRCA gene mutations in cancer

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Endometrial Thickness Measurement for Detecting Endometrial Cancer in Women With Postmenopausal Bleeding: A Systematic Review and Meta-Analysis

Timmermans, A., Opmeer, B. C., Khan, K. S., Bachmann, L. M., Epstein, E., Clark, T. J., Gupta, J. K., Bakour, S. H., van den Bosch, T., van Doorn, H. C., et al. (2010) · Obstetrics & Gynecology

Endometrial and Cervical Cancer TreatmentsGynecological conditions and treatments

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Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: Comparison with expert subjective assessment

Christiansen, F., Epstein, E. L., Smedberg, E., Åkerlund, M., Smith, K., & Epstein, E. (2021) · Ultrasound in Obstetrics & Gynecology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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Ultrasound‐based risk model for preoperative prediction of lymph‐node metastases in women with endometrial cancer: model‐development study

Eriksson, L. S. E., Epstein, E., Testa, A. C., Fischerova, D., Valentin, L., Sladkevicius, P., Franchi, D., Frühauf, F., Fruscio, R., Haak, L. A., et al. (2020) · Ultrasound in Obstetrics & Gynecology

Endometrial and Cervical Cancer TreatmentsOvarian cancer diagnosis and treatment

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