Research
Publications & presentations
Since 2010 our work is focused on factors affecting IVF outcomes, interpretable machine learning for stimulation and trigger timing, AI-assisted embryo selection, embryo assessment. We also conducted large cohort analyses on single embryo transfers in IVF cycles — aligned with the analytics tools we built on this site. Each entry links to the article or meeting (where possible), and to the journal or professional IVF societies websites.
Highlighted themes
Reproductive BioMedicine Online; Fertility and Sterility (full articles & related abstracts) · 2022
Interpretable machine learning for gonadotrophin starting dose and trigger timing during ovarian stimulation
Work with Dr. Fanton and colleagues on interpretable ML models for individualized stimulation dosing, predicting optimal trigger day, and expected-benefit analyses—bridging predictive analytics with clinical decision-making in IVF.
Fertility and Sterility · 2022
AI characterization and ranking of blastocyst-stage embryos from static images
Collaborative study on an AI model for ranking blastocyst images, with sensitivity analyses (e.g., focal plane) and related meeting presentations on bias and generalization in deep learning for embryo assessment.
Human Reproduction; Journal of Assisted Reproduction and Genetics · 2016–2017
High gonadotropin dosage, euploidy, and pregnancy outcomes in PGT cycles with single embryo transfer
Foundational analyses linking stimulation dose, blastocyst morphology, chromosomal status, and clinical outcomes—supporting evidence-based discussion of SET and laboratory variables in PGT.
Fertility and Sterility; Human Reproduction; RBMO · 2015–2020
Morphology, euploidy, and pregnancy in large single-embryo-transfer cohorts
Large retrospective reviews (thousands of embryos/cycles) on morphology vs euploidy, SET outcomes, and predictive modeling for embryo selection—consistent with the themes behind the calculators on this site.
Cambridge University Press — In-vitro fertilization (Elder & Dale) · 2010
Textbook contribution — IVF laboratory methods
Contributions to the standard laboratory reference on IVF techniques.
Complete list
- 47Peer-reviewed
Barash OO, Miller KA, Sessions BR, Abeyta MJ, Baker M, Gangrade BK, Chang Z, Fanton M, Suraj V, VerMilyea MD. Evaluation of artificial intelligence for embryo selection during IVF: a prospective, randomized controlled trial. Fertility and Sterility. 2025 Dec 1;124(6):e49-e50.
- 46Peer-reviewed
Barash OO, Miller KA, Wozniak M, Kaskar K, Sessions BR, Abeyta MJ, Bhakta S, Baker M, Gangrade BK, Chang Z, Fanton M, Suraj V, VerMilyea MD. Evaluation of the effect on ongoing pregnancy rate of using artificial intelligence for embryo prioritization: an interim analysis of a prospective randomized control trial. Fertility and Sterility. 2024 Nov 1;122(4):e347.
- 45Abstract / supplement
Suraj V, Fanton M, Verleger M, Swain JE, Miller KA, Barash O. P-170 Clinical evaluation of an image-based artificial intelligence model for embryo selection: a double-blinded randomized comparative reader study. Human Reproduction. 2024 Jul;39(Supplement_1):deae108.541.
- 44Peer-reviewed
Barash OO, Murillo Armijo F, Cho JH, Suraj V, Loewke K, Swain JE, Miller KA, VerMilyea MD. Clinical evaluation of a machine learning model for embryo selection: a double-blinded randomized comparative reader study. Fertility and Sterility. 2023 Dec 1;120(4):e1.
- 43Peer-reviewed
Chang Z, Cho JH, Sakkas D, Miller KA, VerMilyea M, Barash O, Loewke K. Automated morphology grading of blastocyst stage embryos from a single image using deep learning. Fertility and Sterility. 2023 Dec 1;120(4):e110.
- 42Peer-reviewed
Barash OO, Hinckley MD, Hariton E, Wachs DS, Homer MV. Association between initial β-hCG values and clinical outcomes — a 10,985 cycles review. Fertility and Sterility. 2023 Sep 1;120(1):e62-e63.
- 41Peer-reviewed
Fanton M, Sakkas D, Barash O, Weckstein LN, Copperman AB, Loewke K. An artificial intelligence model to predict upcoming embryology workload for patients undergoing ovarian stimulation. Fertility and Sterility. 2023 Sep 1;120(1):e56-e57.
- 40Peer-reviewed
Fanton M, Nutting V, Rothman A, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman AB, Loewke K. An interpretable machine learning model for individualized gonadotrophin starting dose selection during ovarian stimulation. Reproductive BioMedicine Online. 2022 Dec 1;45(6):1152-9.
- 39Peer-reviewed
Fanton M, Sakkas D, Barash O, Weckstein L, Copperman A, Maeder-York P, Loewke K. An interpretable and generalizable machine learning model for optimizing day of trigger during ovarian stimulation. Fertility and Sterility. 2022 Nov 1;118(5):e44.
- 38Peer-reviewed
Cho JH, Miller KA, Hoffman D, Barash O, Weckstein L, Levy M, Copperman A, Maeder-York P, Loewke K. A stepwise approach for estimating cumulative live birth rates for patients considering IVF. Fertility and Sterility. 2022 Nov 1;118(5):e35.
- 37Peer-reviewed
Fanton M, Nutting V, Solano F, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman AB, Loewke K. An interpretable machine learning model for predicting the optimal day of trigger during ovarian stimulation. Fertility and Sterility. 2022 Jul;118(1):101-8.
- 36Meeting
Cho JH, Brumar CD, Maeder-York P, Barash O, Malmsten J, Zaninovic N, Sakkas D, Miller K, Levy M, VerMilyea MD, Loewke K. 38th Hybrid Annual Meeting of the ESHRE, Milan—Italy, 3–6 July 2022 i271.
- 35Abstract / supplement
Fanton M, Tang J, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman A, Loewke K. P-600 A combined expected benefit analysis of using two machine learning models for optimizing starting gonadotropin dose and day of trigger during ovarian stimulation. Human Reproduction. 2022 Jul;37(Supplement_1):deac107-552.
- 34Abstract / supplement
Tang J, Fanton M, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman A, Loewke K. O-014 An expected benefit analysis of using an interpretable machine learning model for gonadotropin starting dose selection during ovarian stimulation. Human Reproduction. 2022 Jul;37(Supplement_1):deac104-014.
- 33Abstract / supplement
Cho JH, Ehlers A, Brumar C, Maeder-York P, Barash O, Malmsten J, Nikica Z, Sakkas D, Levy M, Miller K, VerMilyea MD. P-173 Large-scale simulation of pregnancy rate improvements using an AI model for embryo ranking. Human Reproduction. 2022 Jul;37(Supplement_1):deac107-168.
- 32Abstract / supplement
Fanton M, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman AB, Loewke K. P-599 An expected benefit analysis of using an interpretable machine learning model for optimizing the day of trigger during ovarian stimulation. Human Reproduction. 2022 Jul;37(Supplement_1):deac107-551.
- 31Abstract / supplement
Cho JH, Brumar CD, Maeder-York P, Barash O, Malmsten J, Zaninovic N, Sakkas D, Miller K, Levy M, VerMilyea MD, Loewke K. P-171 Sensitivity analysis of an embryo grading artificial intelligence model to different focal planes. Human Reproduction. 2022 Jul;37(Supplement_1):deac107-166.
- 30Abstract / supplement
Fanton M, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman AB, Loewke K. An expected benefit analysis of using an interpretable machine learning model for optimizing the day of trigger during ovarian stimulation. Human Reproduction. 2022 Jul 1 (Vol. 37, pp. I470-I470). Oxford Univ Press.
- 29Abstract / supplement
Cho JH, Ehlers A, Brumar C, Maeder-York P, Barash O, Malmsten J, Nikica Z, Sakkas D, Levy M, Miller K, VerMilyea MD. Large-scale simulation of pregnancy rate improvements using an AI model for embryo ranking. Human Reproduction. 2022 Jul 1 (Vol. 37, pp. 272-273). Oxford Univ Press.
- 28Abstract / supplement
Cho JH, Brumar CD, Maeder-York P, Barash O, Malmsten J, Zaninovic N, Sakkas D, Miller K, Levy M, VerMilyea MD, Loewke K. Sensitivity analysis of an embryo grading artificial intelligence model to different focal planes. Human Reproduction. 2022 Jul 1 (Vol. 37, pp. 271-272). Oxford Univ Press.
- 27Abstract / supplement
Fanton M, Tang J, Maeder-York P, Hariton E, Barash O, Weckstein L, Sakkas D, Copperman A, Loewke K. A combined expected benefit analysis of using two machine learning models for optimizing starting gonadotropin dose and day of trigger during ovarian stimulation. Human Reproduction. 2022 Jul 1 (Vol. 37, pp. I470-I470). Oxford Univ Press.
- 26Peer-reviewed
Loewke K, Cho JH, Brumar CD, Maeder-York P, Barash O, Malmsten JE, Zaninovic N, Sakkas D, Miller KA, Levy M, VerMilyea MD. Characterization of an artificial intelligence model for ranking static images of blastocyst stage embryos. Fertility and Sterility. 2022 Mar 1;117(3):528-35.
- 25Meeting
Loewke KE, Nutting VI, Cho JH, Barash OO, Weckstein LN. A machine learning approach for forecasting follicle growth and predicting the optimal day of trigger during ovarian stimulation. ASRM 2021 Scientific Congress & Expo. 2021 Oct 20.
- 24Meeting
Loewke KE, Cho JH, Maeder-York P, Barash OO, Meseguer M, Zaninovic N, Miller KA, Sakkas D, Levy M, VerMilyea M. A generalizable model for ranking blastocyst stage embryos using deep learning. ASRM 2021 Scientific Congress & Expo. 2021 Oct 19.
- 23Meeting
Loewke KE, Cho JH, Maeder-York P, Barash OO, Meseguer M, Malmsten J, Miller KA, Sakkas D, Levy M, VerMilyea M. Identifying potential sources of bias in deep learning models for embryo assessment. ASRM 2021 Scientific Congress & Expo. 2021 Oct 19.
- 22Peer-reviewed
Barash OO, Ivani K, Wachs D, Weckstein LN. Low euploidy rate does not affect clinical outcomes in IVF PGT cycles with single embryo transfer (SET)—a 2391 SETs review. Fertility and Sterility. 2020 Sep 1;114(3):e291-2.
- 21Peer-reviewed
Barash OO, Ivani K, Hinckley MD, Weckstein LN. Association between the number of oocytes retrieved, cancellation rates, and clinical outcomes in IVF PGT cycles with single embryo transfer (SET)—a 2273 cycles review. Fertility and Sterility. 2019 Sep 1;112(3):e177.
- 20Abstract / supplement
Barash O, Ivani K, Hinckley M, Wachs D, Homer M, Reid SP, Weckstein L. Predicting the euploidy status of the embryos by using evolutionary algorithm in IVF PGT cycles-A 10793 embryos review. Human Reproduction. 2019 Jul 1 (Vol. 34, pp. 132-133). Oxford Univ Press.
- 19Peer-reviewed
Barash O, Ivani K, Weckstein L, Hinckley M. High accuracy machine learning predictive model for embryo selection in IVF PGT cycles with single embryo transfers. Fertility and Sterility. 2018 Sep 1;110(4):e372.
- 18Abstract / supplement
Barash OO, Ivani KA, Willman SP, Huen N, Homer MV, Weckstein LN. Model ensembling and synthetic features in PGS cycles with single embryo transfer. Human Reproduction. 2018 Jul 1 (Vol. 33, pp. 417-417). Oxford Univ Press.
- 17Peer-reviewed
O. Barash, S. P. Willman, K. A. Ivani, D. S. Wachs, F. B. Rabara, N. Huen, L. N. Weckstein. Single embryo transfer as an imperative choice for patients over 38 years old in autologous IVF PGS cycles. Reproductive BioMedicine Online. 2018;36:e29-e30.
- 16Peer-reviewed
Barash OO, Hinckley MD, Rosenbluth EM, Ivani KA, Weckstein LN. High gonadotropin dosage does not affect euploidy and pregnancy rates in IVF PGS cycles with single embryo transfer. Human Reproduction. 2017 Oct 12;32(11):2209-17.
- 15Peer-reviewed
Barash O, Ivani K, Huen N, Willman S, Weckstein L. Morphology of the blastocysts is the single most important factor affecting clinical pregnancy rates in IVF PGS cycles with single embryo transfers. Fertility and Sterility. 2017 Sep 1;108(3):e99.
- 14Peer-reviewed
Barash OO, Ivani KA, Willman SP, Rosenbluth EM, Wachs DS, Hinckley MD, Reid SP, Weckstein LN. Association between growth dynamics, morphological parameters, the chromosomal status of the blastocysts, and clinical outcomes in IVF PGS cycles with single embryo transfer. Journal of assisted reproduction and genetics. 2017 Aug 1;34(8):1007-16.
- 13Peer-reviewed
O. Barash, K.A. Ivani, M.D. Hinckley, S.P. Willman, F. Rabara, N. Huen, L.N. Weckstein. Impact of embryo morphology on clinical pregnancy rates in IVF PGS cycles with single embryo transfer. Fertility and Sterility. 2017 Mar 1;107(3):e18-9.
- 12Peer-reviewed
Barash O, Ivani K, Weckstein L, Willman S, Rosenbluth E, Wachs D, Hinckley M. Association between high gonadotropin dosage, euploidy and pregnancy rates in PGT cycles. Fertility and Sterility. 2016 Sep 1;106(3):e154.
- 11Peer-reviewed
Barash O, Ivani K, Willman S, Weckstein L, Rosenbluth E, Wachs D, Hinckley M. Clinical pregnancy rates after elective versus non-elective single embryo transfer in PGT cycles. Fertility and Sterility. 2016 Sep 1;106(3):e25-6.
- 10Abstract / supplement
O. Barash, K. A. Ivani, S.P. Willman, N. Huen, S. C. Lefko, C. F. Mackenzie, L. N. Weckstein. High gonadotropin dosage does not affect euploidy and pregnancy rates in PGT cycles. Abstract book of the 32nd ESHRE Annual Meeting. Hum. Reprod. 2016, Volume 31 (suppl 1): i220.
- 9Peer-reviewed
Barash OO, Ivani KA, Willman SP, Hinckley MD, Wachs DS, et al. (2016) Clinical pregnancy rates after elective versus non-elective single embryo transfer in PGS cycles. JFIV Reprod Med Genet 4:195. doi:10.4172/2375-4508.1000195
- 8Peer-reviewed
Barash O, Ivani K, Willman S, Weckstein L, Rosenbluth E, Wachs D, Hinckley M. Comparison of clinical pregnancy rates after single embryo transfer of day 5 versus day 6 euploid embryo. Fertility and Sterility. 2015 Sep 1;104(3):e94.
- 7Abstract / supplement
O. Barash, K. A. Ivani, N. Huen, S. C. Lefko, C. F. Mackenzie, L. N. Weckstein. Association between blastocyst morphology and euploidy rates in different age groups analyzed by aCGH and SNP PGD. Abstract book of the 31st ESHRE Annual Meeting, Lisbon, Portugal, 14–17 June 2015. Hum. Reprod. (2015) 30 (suppl 1): i379.
- 6Meeting
O. Barash, K. A. Ivani, S. C. Lefko, C. F. Mackenzie, N. Huen, S. P. Willman, L. N. Weckstein. Top quality embryos from patients under 38 years old have euploidy rates similar to euploidy rates in donor oocyte cycles. Preimplantation Genetics Diagnosis International Society, 2015.
- 5Peer-reviewed
Mary deRaime Hinckley, Salustiano Ribeiro, Oleksii Barash. In search of a cost-effective flare protocol for poor responders. Fertility and Sterility. Vol. 103, Issue 2, e32.
- 4Peer-reviewed
O. Barash, K.A. Ivani, S.P. Willman, C. MacKenzie, S.C. Lefko, L.N. Weckstein. Clinical pregnancy rate after single euploid embryo transfer is age independent. Fertility and Sterility. Vol. 103, Issue 2, e10.
- 3Peer-reviewed
O. Barash, K.A. Ivani, S.P. Willman, N. Huen, L.N. Weckstein, S.C. Lefko. Comparison of blastocyst morphology and euploidy rates analyzed by SNP and aCGH PGS – 1003 embryos review. Fertility and Sterility. Vol. 102, Issue 3, e182–e183.
- 2Peer-reviewed
O. Barash, K.A. Ivani, S.P. Willman, N. Huen, L.N. Weckstein, S.C. Lefko. Blastocysts available for biopsy on day 5 are more likely to result in a viable pregnancy. Fertility and Sterility. 2014; Vol. 102, Issue 3, e62.
- 1Book
Elder K, Dale B. In-vitro fertilization. Cambridge University Press; 2010. Contributions on p. 285-287.