A deep learning approach to understanding controlled ovarian stimulation and in vitro fertilization dynamics.

ABSTRACT: Infertility, recognized by the World Health Organization (WHO) as a disease affecting the male or female reproductive system, presents a global challenge due to its impact on one in six individuals worldwide. Given the high prevalence of infertility and the limited available resources in fertility care, infertility creates substantial obstacles to reproductive autonomy and places a considerable burden on fertility care providers. While existing research are exploring to use artificial intelligence (AI) methods to assist fertility care providers in managing in vitro fertilization (IVF) cycles, these attempts fail in accurately predicting specific aspects such as medication dosage and intermediate ovarian responses during controlled ovarian stimulation (COS) within IVF cycles. Our current wo

SUBMITTER: Wang J 

PROVIDER: S-EPMC11885538 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature