Artificial intelligence in the service of intrauterine insemination and timed intercourse in spontaneous cycles.

Journal: Fertility and sterility
PMID: 37490977

Abstract

OBJECTIVE: To develop a machine learning model designed to predict the time of ovulation and optimal fertilization window for performing intrauterine insemination or timed intercourse (TI) in natural cycles.

Authors

  • Michal Youngster
    IVF Unit, Department of Obstetrics and Gynecology, Shamir Medical Center, Zerifin, Israel; Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel. Electronic address: michalyo@gmail.com.
  • Almog Luz
    FertilAi, Ramat Gan, Israel.
  • Micha Baum
    Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel; FertilAi, Ramat Gan, Israel; IVF Unit, Herzliya Medical Centre, Herzliya, Israel; IVF Unit, Department of Obstetrics and Gynecology, Sheba Medical Center, Ramat-Gan, Israel.
  • Rohi Hourvitz
    FertilAi, Ramat Gan, Israel.
  • Shachar Reuvenny
    FertilAi, Ramat Gan, Israel.
  • Ettie Maman
    Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel; FertilAi, Ramat Gan, Israel; IVF Unit, Herzliya Medical Centre, Herzliya, Israel; IVF Unit, Department of Obstetrics and Gynecology, Sheba Medical Center, Ramat-Gan, Israel.
  • Ariel Hourvitz
    IVF Unit, Department of Obstetrics and Gynecology, Shamir Medical Center, Zerifin, Israel; Sackler School of Medicine, Tel Aviv University, Tel-Aviv, Israel; FertilAi, Ramat Gan, Israel.

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