Aging Prediction Modeling Based on Machine Learning with Body Odor Compounds Data

• DOI: 10.9717/kmms.2023.26.2.429
• Publication Date: 2023-03-15T05:57:24Z
• Authors: Chaewon Kim; Daeun Baek; Jinyoung Jang; Hyunhee Lee; Jisook Park; Minseo Park
• Keywords: Population Ageing; Brain Aging

The world’s population is quickly aging due to the increase in life expectancy and decline birth rate. In order solve various social problems caused by a deep understanding of needed. Research on currently active however there hasn’t been much work predicting using machine learning. This study proposes learning algorithm that uses body odor compounds related predicts aging. data was collected from 120 women 20s 70s with participants’ age sweat. After preprocessing, Supervised Learning, we analyzed who showed largest difference degree Decision tree highest classification accuracy about 95%, Cyclopropane, 2-Nonenal, 1-Propene were important result this expected help effective prediction. It can be applied not only personalized healthcare industry but also cosmetics for Korean women.