Alife Health to Present Groundbreaking AI Research at ASRM 2023 Annual Meeting

New research showcases AI’s ability to perform embryo selection and the synergy of AI tools in predicting ovarian stimulation outcomes

San Francisco /October 9th, 2023

Alife Health, a technology company building AI tools to advance fertility care, is excited to unveil new research at the acclaimed American Society for Reproductive Medicine (ASRM) Annual Meeting in October 2023, in New Orleans, LA. The company will be presenting two oral presentations and two poster sessions showcasing the use of AI to improve IVF.

Alife’s innovative software platform, Alife Assist™, streamlines the entire IVF journey, offering personalized, data-driven insights that empower fertility specialists to practice precision medicine like never before. The ASRM Annual Meeting will serve as the stage for Alife to present its latest research and innovations.

The first presentation, which is nominated for the 2023 Congress Prize Paper, evaluates the performance of a machine learning model for ranking blastocyst-stage embryos using a double-blinded randomized comparative reader study. Researchers found that the machine learning model was able to select the top embryo for transfer with similar performance to experienced embryologists. Such a model could allow for objective and consistent embryo selection using morphology grades and day of development, a tool that could drastically enhance clinic standardization and quality control. The oral presentation and following panel event on the study are as follows:

"Clinical Evaluation Of A Machine Learning Model For Embryo Selection: A Double-Blinded Randomized Comparative Reader Study" Oral presentation by Oleksii O. Barash, Ph.D, on Monday, October 16, 2023, 10:45 AM, Room 213

Live panel discussion and Q&A with top embryologists Join Jason E Swain, PhD., Matthew “Tex” VerMilyea, H.C.L.D, PH.D., and Oleksii O. Barash, Ph.D. to review the evidence on Tuesday, October 17, 10:15am, Booth 840

The second presentation evaluates the integration of two independently-developed AI tools: (1) automated follicle measurements from MyCycleClarity, and (2) predictions of number of eggs retrieved using Alife’s Stim Assist™. This preliminary study shows the synergy of two distinct machine learning tools and how their combined use in practice may increase the accuracy for predicting the number of eggs retrieved during ovarian stimulation. The oral presentation on the study is as follows:

“Evaluating the integration of two independently-developed artificial intelligence tools for predicting outcomes in ovarian stimulation” Oral presentation by Michael Fanton, Ph.D, on Tuesday, October 17, 2023, 3:52 PM, Room 211

Alife researchers are also presenting two poster sessions, including:

“Automated morphology grading of blastocyst stage embryos from a single image using deep learning” Poster session with Zeyu Chang, Monday, October 16, 2023, 11:25 AM, Room 214

“Serum Progesterone Prior To And After Frozen Embryo Transfer Cycles Do Not Correlate With Live Birth Rates In Programmed Cycles Utilizing Intramuscular Progesterone For Luteal Support” Poster session by Meghan Uki Yamasaki, DO, on Monday, October 16, 2023, 11:30 AM, Room 232

Conference attendees are invited to visit Booth 840 to explore the transformative capabilities of Alife’s AI software platform, Alife Assist™. To learn more about the company’s ASRM 2023 events or to schedule a one-on-one product demonstration, please visit

About Alife Health

Alife’s mission is to modernize and personalize the IVF process with cutting edge artificial intelligence technology to improve outcomes and care for all. The company has built a consortium of partnerships with the top clinics and most renowned physicians to bring significant clinical improvements to patients globally. Founded by Paxton Maeder-York in 2020, the company is based in San Francisco and backed by top tier venture capital investors including Lux Capital, Union Square Ventures, and Maveron.

PRESS CONTACT: Jamie Gray,, 310-699-3163