Analysis for Women’s’ Menstrual Health Disorders Using Artificial Intelligence

Abstract

This paper presents some developments related to a project aiming to develop an AI-based model which can determine the possible ovulation dates as well as possibility of some health risks based on the input of a woman for a finite number of menstrual cycles. In some earlier papers, the AI schemes for some health risks, such as PMS, LPD, are already discussed. In this paper, additionally the schemes for hypothyroidism and polycystic ovary syndrome (PCOS) are presented. The model is based on a ontology of medical concepts, mathematical formulations of which are designed based on the data obtained from different users over a finite number of menstrual cycles and usual relationships among different parameters determining such concepts. The mathematical formulations of the concerned medical concepts are developed by using some notions of fuzzy linguistic labels and comparators.