Math, Science, and Health: Analysis on Women Health Issues: An Algorithmic Perspective

Math, Science, and Health: Analysis on Women Health Issues: An Algorithmic Perspective
Author(s):
Shivani Ramakrishnan, Fouzia Fathima A.M, Jagatheeswari.M
Keywords:
Predictive Analysis, Cancer, Anemia, PCOS, Machine Learning
Abstract
There has been a lack of research and detailed studies on women’s health and diseases that predominantly affect them. In this paper, we aim to examine certain conditions which mainly affect women and identify the factors which play a significant role in their occurrence. For this study, diseases such as Anemia, breast cancer, and Polycystic ovary syndrome (PCOS) were considered. Machine learning models and algorithms such as XGboost and Random Forest Classifier were used to find top causes. Model performance and results were examined for each of the diseases, and data interpretation was made with the help of SHAP plots. The results showed that a focused study on women's health yielded less biased and accurate results.
Article Details
Unique Paper ID: 153563 Publication Volume & Issue: Volume 8, Issue 7 Page(s): 485 - 488
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org