Application using Machine Learning to Promote Women’s Personal Health

The use of mobile applications in healthcare is on the rise among women, and these applications play a significant role. They visit the gynaecologist for the problems like menstrual irregularities, infertility, PCOD(Polycystic Ovarian Disease), PCOS, menopause. Instead they can clarify their doubts regarding gynaecology via a web application. The purpose of the proposed model is to ensure the women’s personal health using web application. Currently a web based application is developed for women to track LMP(last menstrual period).The menstrual cycle is tracked by dividing observations by the cycle’s length. Using a survey, the most frequently asked questions are complied and answered by the gynaecologists. Moreover, there is information about how to cope up with these problems. A probabilistic machine learning algorithm is used for text classification and a database is created to store the user’s data and their activity. A graphic user interface (GUI) makes it easy for the user to access and understand the information given by the mobile application. The application retains the user’s details if they are not filled out by the user. Highly engaged users need to be given more choices and need more supported navigation within the application. The proposed model also suggests a doctor when a problem is identified. Currently, the existing system focuses exclusively on menstruation and the possibility of getting pregnant. In the question section, users are not given much opportunity to clarify their doubts. There are predetermined question, users can see only these predetermined questions and answers. There is no option to ask their own question. Women’s age and marital status are not taken into consideration.