A research group led by Professor Yoshiharu Yokokawa at Shinshu University used Multi-Sigma® for data analysis in their study, “Examination of Social Participation in Older Adults Undergoing Frailty Health Checkups Using Deep Learning Models.”
The study used machine learning models to examine social participation among older adults undergoing frailty health checkups, focusing on the issue of frailty and its impact on social participation. Multi-Sigma® was used to build a deep neural network (DNN) model for predicting social participation among the participants.
Approximately 300 older adults participated in the study. Using 18 data items covering physical, cognitive, social, and other factors, the researchers compared three machine learning models.
The DNN model built using Multi-Sigma® demonstrated balanced predictive performance and showed high sensitivity in identifying older adults who participated in social activities.
The findings are expected to offer new possibilities for efforts to prevent social isolation among older adults and extend healthy life expectancy.
For further details, please refer to the paper below.
Publication Details
Title
Examination of Social Participation in Older Adults Undergoing Frailty Health Checkups Using Deep Learning Models
Authors
Yoshiharu Yokokawa et al.
Journal
Geriatrics 2025, 10(5), 124
Publication Year
2025
