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@article{ART003017289},
author={Choi, Hyunchul and Chiho Yoon and Sae Bom Lee},
title={Cognitive Impairment Prediction Model Using AutoML and Lifelog},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2023},
volume={28},
number={11},
pages={53-63},
doi={10.9708/jksci.2023.28.11.053}

TY - JOUR
AU - Choi, Hyunchul
AU - Chiho Yoon
AU - Sae Bom Lee
TI - Cognitive Impairment Prediction Model Using AutoML and Lifelog
JO - Journal of The Korea Society of Computer and Information
PY - 2023
VL - 28
IS - 11
PB - The Korean Society Of Computer And Information
SP - 53
EP - 63
SN - 1598-849X
AB - This study developed a cognitive impairment predictive model as one of the screening tests for preventing dementia in the elderly by using Automated Machine Learning(AutoML). We used ‘Wearable lifelog data for high-risk dementia patients’ of National Information Society Agency, then conducted using PyCaret 3.0.0 in the Google Colaboratory environment. This study analysis steps are as follows; first, selecting five models demonstrating excellent classification performance for the model development and lifelog data analysis. Next, using ensemble learning to integrate these models and assess their performance. It was found that Voting Classifier, Gradient Boosting Classifier, Extreme Gradient Boosting, Light Gradient Boosting Machine, Extra Trees Classifier, and Random Forest Classifier model showed high predictive performance in that order. This study findings, furthermore, emphasized on the the crucial importance of 'Average respiration per minute during sleep' and 'Average heart rate per minute during sleep' as the most critical feature variables for accurate predictions. Finally, these study results suggest that consideration of the possibility of using machine learning and lifelog as a means to more effectively manage and prevent cognitive impairment in the elderly.
KW - AutoML;Ensemble learning;Prediction model;Lifelog;Cognitive impairment
DO - 10.9708/jksci.2023.28.11.053
ER -

Choi, Hyunchul, Chiho Yoon and Sae Bom Lee. (2023). Cognitive Impairment Prediction Model Using AutoML and Lifelog. Journal of The Korea Society of Computer and Information, 28(11), 53-63.

Choi, Hyunchul, Chiho Yoon and Sae Bom Lee. 2023, "Cognitive Impairment Prediction Model Using AutoML and Lifelog", Journal of The Korea Society of Computer and Information, vol.28, no.11 pp.53-63. Available from: doi:10.9708/jksci.2023.28.11.053

Choi, Hyunchul, Chiho Yoon, Sae Bom Lee "Cognitive Impairment Prediction Model Using AutoML and Lifelog" Journal of The Korea Society of Computer and Information 28.11 pp.53-63 (2023) : 53.

Choi, Hyunchul, Chiho Yoon, Sae Bom Lee. Cognitive Impairment Prediction Model Using AutoML and Lifelog. 2023; 28(11), 53-63. Available from: doi:10.9708/jksci.2023.28.11.053

Choi, Hyunchul, Chiho Yoon and Sae Bom Lee. "Cognitive Impairment Prediction Model Using AutoML and Lifelog" Journal of The Korea Society of Computer and Information 28, no.11 (2023) : 53-63.doi: 10.9708/jksci.2023.28.11.053

Choi, Hyunchul; Chiho Yoon; Sae Bom Lee. Cognitive Impairment Prediction Model Using AutoML and Lifelog. Journal of The Korea Society of Computer and Information, 28(11), 53-63. doi: 10.9708/jksci.2023.28.11.053

Choi, Hyunchul; Chiho Yoon; Sae Bom Lee. Cognitive Impairment Prediction Model Using AutoML and Lifelog. Journal of The Korea Society of Computer and Information. 2023; 28(11) 53-63. doi: 10.9708/jksci.2023.28.11.053

Choi, Hyunchul, Chiho Yoon, Sae Bom Lee. Cognitive Impairment Prediction Model Using AutoML and Lifelog. 2023; 28(11), 53-63. Available from: doi:10.9708/jksci.2023.28.11.053

Choi, Hyunchul, Chiho Yoon and Sae Bom Lee. "Cognitive Impairment Prediction Model Using AutoML and Lifelog" Journal of The Korea Society of Computer and Information 28, no.11 (2023) : 53-63.doi: 10.9708/jksci.2023.28.11.053