A systematic meta-analysis on the role of artificial intelligence and machine learning in detection of gynaecological disorders

Authors

  • Jyoti Nandalwar
  • Pradip Jawandhiya

DOI:

https://doi.org/10.6977/IJoSI.202502_9(1).0004

Keywords:

Artificial Intelligence, Gynecological Cancer, Machine Learning, MRI, Ultrasound

Abstract

Gynaecological disorder is a serious health issue that affects women's health globally. The use of Artificial Intelligence (AI) or Machine learning (ML) techniques has gained the attention of researchers for the detection and diagnosis of gynaecological disorders such as cancer. This paper aims to provide insight into the role of AI in gynaecological disorder diagnosis. This paper also provides a systematic analysis of several AI/ML approaches that are being employed. The paper investigates how ML algorithms can extract characteristics from MRI images and how to use ML to extract and recognize the features from medical images such as MRI, ultrasound, CT-scans, etc. for early detection of gynaecological tumors and provide more personalized risk assessment. However, it is observed that there will be a significant impact of the advancement of AI/ML on medical technology in the future. Therefore, this paper presents a significant contribution to future medical applications and innovations.

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Published

2025-02-19

Issue

Vol. 9 No. 1 (2025): International Journal of Systematic Innovation

Section

Regular full papers

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