Leveraging artificial intelligence for advancements in reproductive health

Afr J Reprod Health. 2024 Nov 30;28(11):216-217. doi: 10.29063/ajrh2024/v28i11.21.

Abstract

We are writing to address the growing interest in the role of artificial intelligence (AI) within healthcare, particularly in the field of reproductive health. As technology continues to evolve, AI offers an unprecedented opportunity to transform how we diagnose, treat, and improve access to reproductive services, especially in underserved communities. AI-driven tools, supported by machine learning and big data analytics, are already demonstrating their potential in enhancing outcomes in reproductive health. These tools can predict fertility outcomes with impressive accuracy, optimize in vitro fertilization (IVF) success rates, and identify early signs of reproductive disorders, such as endometriosis, polycystic ovary syndrome (PCOS), and ovarian cancer. By analyzing biomarkers, medical histories, and lifestyle factors, AI algorithms empower healthcare providers to deliver personalized and effective treatment plans tailored to individual needs.

MeSH terms

  • Artificial Intelligence*
  • Female
  • Fertilization in Vitro / methods
  • Humans
  • Machine Learning
  • Polycystic Ovary Syndrome / therapy
  • Reproductive Health*