Automation and Artificial Intelligence: Is Cutting-Edge Research Ready for Prime Time?

David Sable, MD

Nikica Zaninovic, PhD


Sunday, March 27
9:30 AM – 11:00 AM

 0.75 CME

Session Description:

An examination of the opportunities to use advanced data collection and management to improve efficiency and outcomes in the in vitro fertilization (IVF) process. As we evolve from a clinic-specific “we do it our way” model towards industry-wide best practices, how do we best use 21st century computing power, big data analysis, predictive analytics and advanced engineering to process optimize our way to ever-improving care and vastly expanded access?

ART is one of the fastest-growing fields in medicine. Besides the advancements in hormonal stimulation and treatment regimes, the laboratory aspect of IVF emerged in science and especially technology. The emphasis on future IVF treatments and laboratory procedures emphasizes the non-invasive methods of embryo evaluation and selection. The application of Artificial Intelligence (AI) in daily life prompts us to evaluate this technology in this context. The AI is one of the primary candidates to drive future IVF in the lab and all IVF procedures. The benefit of AI technology involves “big data” analysis, objectivity, standardization, precision, and automatization. The most advancement of AI application is in the IVF lab, where technology can be used to enhance our ability to select the “best” viable embryo objectively. As a new technology, it is essential to evaluate it on a large scale. The AI technology will also enable us to standardize patient reproductive potential clinical parameters and objectively predict each patient reproductive outcome per cycle. Ultimately, AI will help us to achieve the personalized and precision medicine needed in our field.   

Session Objectives:

  1. Identify the specific challenges that IVF collection poses for isolating and assessing the effectiveness of innovation in ART

  2. Discuss how automation and AI applied to specific tasks can improve processes and/or outcomes

  3.  Identify the value proposition of specific technologies

  4. List the basic principles of AI and machine learning.

  5. Describe how to manage “big data” and application of AI in the clinical laboratory and IVF practice

  6. Discuss how to integrate AI applications in the laboratory and clinical parts of IVF