Press

Grants and Recognitions

  • State of California CASCADE Grant

Accelerator Programs

Media Features

Podcast Appearances

  • Talent Finders – Kerrin Black Interview
  • Interview with Alice Crisci of MedAnswers
  • If These Ovaries Could Talk Podcast
  • Recurring Guest on BEAT INFERTILITY PODCAST
    • Inside the IVF Lab
    • Artificial Intelligence in Assisted Reproduction
    • Epigenetics 101
    • Evaluating Your IVF Lab
  • Recurring Guest on The Egg Whisperer
  • Recurring Guest on LORI METZ PODCAST
    • What Goes On in the Lab and the Impact of COVID-19
    • ABCs of Creating an Embryo in the Lab with Carol Lynn Curchoe

Research and Publications

  • Peer-Reviewed Data Publications
    • Dimitriadis, I., Bormann, C. L., & Sakkas, D. (2019). Artificial intelligence-enabled system for embryo classification and selection based on image analysis. Fertility and Sterility, 112(4), e19. https://doi.org/10.1016/j.fertnstert.2019.07.54
    • Khosravi, P., Kazemi, E., Zhan, Q., Malmsten, J. E., Toschi, M., Zisimopoulos, P., Sigaras, A., Lavery, S., Cozzubbo, T., Rosenwaks, Z., Elemento, O., & Zaninovic, N. (2019). Improved monitoring of human embryo culture conditions using a deep learning-based image analysis system. Fertility and Sterility, 112(4), e52. https://doi.org/10.1016/j.fertnstert.2019.07.200
    • Khosravi, P., Kazemi, E., Zhan, Q., Malmsten, J. E., Toschi, M., Zisimopoulos, P., Sigaras, A., Lavery, S., Cozzubbo, T., Rosenwaks, Z., Elemento, O., & Zaninovic, N. (2019). Automated quality assessment of individual embryologists performing ICSI using deep learning-enabled fertilization and embryo grading technology. Fertility and Sterility, 112(4), e53. https://doi.org/10.1016/j.fertnstert.2019.07.201
  • Abstracts Presented at Scientific Symposia
    • Curchoe, C. L., & Bormann, C. L. (2018). Artificial intelligence and machine learning in reproductive medicine and embryology: A systematic review. Fertility and Reproductive Medicine, Abstract 32. http://cme-utilities.com/mailshotcme/FRM/2018/Abstracts/32.pdf
    • Khosravi, P., Kazemi, E., Zhan, Q., Malmsten, J. E., Toschi, M., Zisimopoulos, P., Sigaras, A., Lavery, S., Cozzubbo, T., Rosenwaks, Z., Elemento, O., & Zaninovic, N. (2019). Improved monitoring of human embryo culture conditions using a deep learning-based image analysis system. Fertility and Sterility, 112(4), e52. https://doi.org/10.1016/j.fertnstert.2019.07.200

    • Khosravi, P., Kazemi, E., Zhan, Q., Malmsten, J. E., Toschi, M., Zisimopoulos, P., Sigaras, A., Lavery, S., Cozzubbo, T., Rosenwaks, Z., Elemento, O., & Zaninovic, N. (2019). Automated quality assessment of individual embryologists performing ICSI using deep learning-enabled fertilization and embryo grading technology. Fertility and Sterility, 112(4), e53. https://doi.org/10.1016/j.fertnstert.2019.07.201

    • Curchoe, C. L., & Bormann, C. L. (2019). Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018. Journal of Assisted Reproduction and Genetics, 36(4), 591–600. https://doi.org/10.1007/s10815-019-01408-x