Prediction of the time to pregnancy by kernel density estimation on lifestyle questionnaire
Current pregnancy measures can be classified into three types: natural pregnancy, artificial insemination, and in vitro fertilization. For those who are trying to get pregnanct, however, it is difficult to judge when they should switch from natural pregnancy to other methods because the factors that contribute to pregnancy are usually not clear. This paper presents a personalized method to estimate the time to pregnancy (TTP) for a natural conception by using kernel density estimation and k-nearest neighbor. Using this method, we can provide suggestions and a TTP estimation to guide decisions on which methods and actioins are suitable for those willing to conceive. In addition, we developed a user-friendly GUI system that can show the probability of the TTP and provide feedback through tips without requiring user expertise.