F, C., EL, E., E, S., M, Å., K, S., & E, E. (2021). Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: Comparison with expert subjective assessment. Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology, 57(1), 155. https://doi.org/10.1002/uog.23530
Chicago Style (17th ed.) CitationF, Christiansen, Epstein EL, Smedberg E, Åkerlund M, Smith K, and Epstein E. "Ultrasound Image Analysis Using Deep Neural Networks for Discriminating Between Benign and Malignant Ovarian Tumors: Comparison with Expert Subjective Assessment." Ultrasound in Obstetrics & Gynecology : The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology 57, no. 1 (2021): 155. https://doi.org/10.1002/uog.23530.
MLA (9th ed.) CitationF, Christiansen, et al. "Ultrasound Image Analysis Using Deep Neural Networks for Discriminating Between Benign and Malignant Ovarian Tumors: Comparison with Expert Subjective Assessment." Ultrasound in Obstetrics & Gynecology : The Official Journal of the International Society of Ultrasound in Obstetrics and Gynecology, vol. 57, no. 1, 2021, p. 155, https://doi.org/10.1002/uog.23530.
