Study shows potential of AI model in improving ovarian stimulation decisions in IVF treatment

A groundbreaking study has demonstrated the potential of AI in optimising the ovarian stimulation process for IVF treatment.

The study, led by Dr Chelsea Canon, a reproductive endocrinologist and infertility specialist for RMA of New York, was a multi-center, prospective analysis of AI’s impact on IVF outcomes.

The Alife software, known as Stim Assist, provides physicians with personalised recommendations based on patient-specific characteristics and follicle growth.

This study is the first to prospectively investigate the clinical outcomes of IVF patients when clinicians utilised AI software to assist in determining the optimal starting dose of follicle-stimulating hormone (FSH) and the timing of trigger injection.

“The results of our study are incredibly promising,” said Dr Eric Flisser, one of the lead authors of the study.

“We found a trend towards improved egg yield and a reduction in FSH usage when physicians used Alife’s Stim Assist. This suggests that AI has the potential to refine the starting dose of FSH and narrow down the timing of the trigger injection during ovarian stimulation, ultimately benefiting patients by optimising the number of mature oocytes retrieved and reducing medication costs.”

Dr Alan B Copperman, CEO of RMA of New York and a collaborator of the study, said: “The use of AI in IVF represents a significant advancement in reproductive medicine.

“By leveraging AI to optimise ovarian stimulation decisions, we can potentially improve IVF outcomes and streamline the treatment process for patients.”

The study, which involved 291 patients undergoing IVF treatment at two clinics in the US, underscores the potential of AI to revolutionise the field of assisted reproductive technology.

However, the researchers emphasised the need for further studies to validate these findings and explore the broader application of AI in IVF treatment.