Press

Grants and Recognitions

• State of California CASCADE Grant

Certification

Carol Lynn Curchoe, PhD, HCLD (ABB), is a board-certified IVF Laboratory Director and currently serves as Laboratory Director for multiple reproductive laboratories, including RRC – The IVF Laboratory, Poma Fertility, and CryoMate. She provides scientific leadership and laboratory oversight supporting clinical excellence, quality systems, and best practices in assisted reproductive technology.

Accelerator Programs

• Ad Astra Bootcamp
  • Meet the Ad Astra Spring 2020 Cohort
  • San Diego Metro Reviews the Ad Astra Graduates
  • Forbes on Programs Supporting AI Startups

Media Features

• Denver Albrecht Women on ART Compass in the Clinic
• Digital Health Buzz: AI for IVF
• Digital Quality Control and Assurance for the IVF Lab
• Quality Control and Assurance for IVF in The Cloud
• Scientific American Blog Post on AI for IVF
• Guest Blog Post on Embryo Freezing
• Meet Your Embryo’s First Babysitter
• A Great Grey Rhino in the Room: The Human Capital Conundrum in ART
• Experts Anticipate Widespread Use of Artificial Intelligence in IVF
• IVF quality control in the cloud

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
  • Patriot Conceptions. 2021. “In Conversation with Dr. Carol Lynn Curchoe, Senior Embryologist and Founder ARTCompass.” Patriot Conceptions Blog, February 1, 2021. https://patriotconceptions.com/social-media/blog/in-conversation-with-dr-carol-lynn-curchoe-senior-embryologist-and-founder-artcompass/
  • Curchoe, C. L. (2022). Meetings that matter: time to put artificial intelligence on the ART roadmap. Journal of Assisted Reproduction and Genetics, 39, 1493–1496. https://doi.org/10.1007/s10815-022-02520-1

  • Curchoe, C. L., Chang, T. A., Trolice, M. P., Telfer, E. E., Quaas, A. M., Kearns, W. G., Stern, J. E., & Albertini, D. F. (2022). Protecting life in a time of war. Journal of Assisted Reproduction and Genetics, 39(3), 555–557. https://doi.org/10.1007/s10815-022-02463-7

  • Curchoe, C. L. (2022). For whom the artificial intelligence bell tolls: Preimplantation genetic testing for aneuploidy, does it toll for thee? Fertility and Sterility, 117(3), 536–538. https://doi.org/10.1016/j.fertnstert.2022.01.005

  • Curchoe, C. L. (2022). The blockchain and decentralized manipulation of confidential information: Uses in medical healthcare and assisted reproduction. Journal of Assisted Reproduction and Genetics. https://pubmed.ncbi.nlm.nih.gov/34984600/

  • Curchoe, C. L. (2021). The paper chase and the big data arms race. Journal of Assisted Reproduction and Genetics, 38(7), 1613–1615. https://doi.org/10.1007/s10815-021-02198-x

  • Trolice, M. P., Curchoe, C. L., & Quaas, A. M. (2021). Artificial intelligence—the future is now. Journal of Assisted Reproduction and Genetics, 38(7), 1607–1612. https://pmc.ncbi.nlm.nih.gov/articles/PMC8260235/

  • Curchoe, C. L., Flores-Saiffe Farias, A., Mendizabal-Ruiz, G., & Chavez-Badiola, A. (2020). Evaluating predictive models in reproductive medicine. Fertility and Sterility, 114(5), 921–926. https://doi.org/10.1016/j.fertnstert.2020.09.159

  • Curchoe, C. L., Malmsten, J., Bormann, C. L., et al. (2020). Predictive modeling in reproductive medicine: Where will the future of artificial intelligence research take us? Fertility and Sterility, 114(5), 934–940. https://pmc.ncbi.nlm.nih.gov/articles/PMC7550613/

  • Curchoe, C. L. (2020). All models are wrong, but some are useful. Journal of Assisted Reproduction and Genetics, 37(10), 2389–2391. https://doi.org/10.1007/s10815-020-01895-3

  • Bormann, C. L., Curchoe, C. L., et al. (2020). Performance of a deep learning-based neural network in the selection of human blastocysts for implantation. Fertility and Sterility, 114(3), 584–593. https://pubmed.ncbi.nlm.nih.gov/32930094/

  • Curchoe, C. L., et al. (2021). Should there be an “AI” in TEAM? Embryologists’ selection of high-implantation-potential embryos improves with the aid of an artificial intelligence algorithm. Fertility and Sterility, 116(4), 1011–1020. https://pubmed.ncbi.nlm.nih.gov/34535847/

  • Curchoe, C. L., et al. (2021). Deep learning early warning system for embryo culture conditions and embryologist performance in the ART laboratory. Fertility and Sterility, 115(6), 1524–1533. https://pmc.ncbi.nlm.nih.gov/articles/PMC8260235/

  • 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

  • Curchoe, C. L. (Ed.). (2021). The Thin Pink Line: Regulating Reproduction. Nova Science Publishers. https://novapublishers.com/shop/the-thin-pink-line-regulating-reproduction/

  • Curchoe, C. L. (2015). The power of mentoring. Science, 350(6259), 478. https://science.sciencemag.org/content/350/6259/478

  • Curchoe, C. L. (2012). Method for tracking core-contributed publications. Journal of Biomolecular Techniques, 23(4), 140–146. https://pubmed.ncbi.nlm.nih.gov/23204927/

  • Curchoe, C. L., et al. (2012). hESC-derived neuro-epithelial rosettes recapitulate early mammalian neurulation events: An in vitro model. Stem Cell Research, 8(1), 43–54. https://pubmed.ncbi.nlm.nih.gov/22265743/

  • Curchoe, C. L., et al. (2009). Hypomethylation trends in the intergenic region of the imprinted IGF2 and H19 genes in cloned cattle. Animal Reproduction Science, 116(1–2), 88–98. https://pubmed.ncbi.nlm.nih.gov/19282114/

  • Curchoe, C. L., et al. (2009). Nicotinamide rescues human embryonic stem cell-derived neuroectoderm from parthanatic cell death. Stem Cells, 27(9), 2102–2113. https://pubmed.ncbi.nlm.nih.gov/19544437/

  • Curchoe, C. L., et al. (2008). Genetic imprinting of H19 and IGF2 in domestic pigs (Sus scrofa). Animal Biotechnology, 19(2), 101–112. https://pubmed.ncbi.nlm.nih.gov/18228173/

  • Curchoe, C. L., et al. (2005). Promoter-specific expression of the imprinted IGF2 gene in cattle (Bos taurus). Biology of Reproduction, 73(6), 1114–1124. https://pubmed.ncbi.nlm.nih.gov/16120826/

  • Curchoe, C. L., et al. (2005). Meat and milk compositions of bovine clones. Proceedings of the National Academy of Sciences, 102(18), 6261–6266. https://pubmed.ncbi.nlm.nih.gov/15829585/

  • Curchoe, C. L., et al. (2010). Early acquisition of neural crest competence during hESCs neuralization. PLOS ONE, 5(9), e12990. https://pubmed.ncbi.nlm.nih.gov/21085480/

  • Curchoe, C. L., & Manor, U. (2017). Actin cytoskeleton-mediated constriction of membrane organelles via endoplasmic reticulum scaffolding. ACS Biomaterials Science & Engineering, 3(11), 2727–2732. https://doi.org/10.1021/acsbiomaterials.6b00802

  • Curchoe, C. L. (2018). Pomp and circumstance: Making the case for CRISPR. The CRISPR Journal, 1(4), 304–306. https://doi.org/10.1089/crispr.2018.29030.oxf

  • Curchoe, C. L. (n.d.). Curchoe: Consider this. Fertility and Sterility Dialog. https://www.fertstertdialog.com/posts/40618-curchoe-consider-this

  • Curchoe, C. L., et al. (2016). Hybrid glucose/O₂ biobattery and supercapacitor utilizing a pseudocapacitive dimethylferrocene redox polymer at the bioanode. ACS Energy Letters, 1(6), 1246–1251. https://doi.org/10.1021/acsenergylett.6b00225

• 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

  • Curchoe, C. L., Bormann, C., Hammond, E., Salter, S., Timlin, C., Blankenship Williams, L., Gilboa, D., Seidman, D., Campbell, A., & Morbeck, D. (2023). Assuring quality in assisted reproduction laboratories: Assessing the performance of ART Compass—a digital art staff management platform. Journal of Assisted Reproduction and Genetics, 40, 265–278. https://doi.org/10.1007/s10815-023-02713-2

  • Curchoe, C. L., & Bormann, C. L. (2023). Dish dilemma: ART Compass mobile application survey of embryo culture dish preparation. Fertility and Sterility, 119(4), e12. https://doi.org/10.1016/j.fertnstert.2023.04.012

  • Curchoe, C. L. (2021, June 24). Digital QA – The future of ART lab management. College of Reproductive Biology (CRB) Newsletter. Retrieved from https://www.aab.org/NewsBot.asp?MODE=VIEW&ID=694

  • Curchoe, C. L., & Bormann, C. L. (2023). Dish dilemma: ART Compass mobile application survey of embryo culture dish preparation. Fertility and Sterility, 119(4), e13. https://doi.org/10.1016/j.fertnstert.2023.04.013

  • Curchoe, C. L., & Bormann, C. L. (2024). Fertility and Sterility, 120(1), 123–130. https://doi.org/10.1016/j.fertnstert.2024.01.702

  • Curchoe, C. L., & Bormann, C. L. (2022). Fertility and Sterility, 118(6), 1150–1157. https://doi.org/10.1016/j.fertnstert.2022.11.675

  • Curchoe, C. L., & Bormann, C. L. (2023). Dish dilemma: ART Compass mobile application survey of embryo culture dish preparation. Fertility and Sterility, 119(4), e13. https://doi.org/10.1016/j.fertnstert.2023.04.013

  • Curchoe, C. L., & Bormann, C. L. (2022). Fertility and Sterility, 118(3), 600–607. https://doi.org/10.1016/j.fertnstert.2022.09.928