Building Melasma Prediction Model Using Catboost Algorithm

Abstract

This study aims to build predict Melasma model based on Catboost machine learning algorithm on users' data combined with medical practice data community by dermatologists to predict the disease and make some necessary recommendations in the patient screening. This study also helps reduce treatment costs and supports remote patient treatment. In this study, we built a prediction melasma model using Catboost machine learning algorithm to assist dermatolo-gists in predicting a person's risk of Melasma after entering his/her community information. People can use this model through an application to track their risk of Melasma. We built a dataset with relevant information combined input community data with the expertise of Melasma specialists to predict Melasma. Based on this dataset, we have statistically described the data characteristics as well as the correlated data parameters that may cause Melasma, then we use the CatBoost machine learning algorithm to build a prediction model to predict whether a person is infected to Melasma or not. The obtained results are going to be applied to assist in predicting whether a person may have Melasma with the input of community information combined with medical practice knowledge about the disease. From this result, it is possible to continue researching and applying artificial intelligence to support diagnosis and treatment of Melasma.