Application of Artificial Intelligence for Diagnosing Tumors in the Female Reproductive System: A Systematic Review

• Abdel Wahed , Mutaz ^[2] ; Alqaraleh, Muhyeeddin ^[1] ; Salem Alzboon , Mowafaq ^[2] ; Subhi Al-Batah , Mohammad ^[2]
  1. [1] Zarqa University

     Zarqa University

     Jordania

     
  2. [2] Jadara University, Computer Science, Irbid, Jordan
• Localización: Multidisciplinar (Montevideo), ISSN-e 3046-4064, Nº. 3, 2025 (Ejemplar dedicado a: Multidisciplinar (Montevideo))
• Idioma: inglés
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• Resumen

  • The diagnosis of tumors in the female reproductive system is crucial for effective treatment and patient outcomes. The advent of artificial intelligence (AI) has introduced new possibilities for enhancing diagnostic accuracy and efficiency. A comprehensive search across PubMed, Scopus, and Web of Science for articles published from 2018 to 2023 on artificial intelligence (AI), machine learning (ML), deep learning (DL), and convolutional neural networks (CNN) in diagnosing cancers of the female reproductive system yielded 15,900 articles. After a rigorous screening process excluding conference proceedings, book chapters, reports, non-English publications, and duplicates, 98 unique peer-reviewed journal articles remained. These were further assessed for relevance and quality, resulting in the final inclusion of 29 high-quality articles. The review includes a summary of various AI methodologies used, their diagnostic accuracy, and comparative performance against traditional diagnostic methods. The findings indicate a significant improvement in diagnostic precision and efficiency when AI is employed. AI holds substantial promise for enhancing the diagnosis of tumors in the female reproductive system. Future research should focus on larger-scale studies and the integration of AI into clinical workflows to fully realize its potential