원문정보
초록
영어
Given the surge in the elderly population, and increasing in dementia cases, there is a growing interest in digital therapies that facilitate steady remote treatment. However, in the cognitive assessment of digital therapies through clinical trials, the absence of log data as an essential evaluation factor is a significant issue. To address this, we propose a solution of utilizing weighted derived variables based on high-importance variables' accuracy in log data utilization as an indirect cognitive assessment factor for digital therapies. We have validated the effectiveness of this approach using machine learning techniques such as XGBoost, LGBM, and CatBoost. Thus, we suggest the use of log data as a rapid and indirect cognitive evaluation factor for digital therapy users.
목차
1. INTRODUCTION
2. RELATED WORK
3. METHOD
3.1 Data Collection
3.2 Data Preprocessing
3.3 Modeling
3.4 Creation of CogScore, A New Derived Variable for Cognitive Ability
4. RESULTS AND DISCUSSION
5. CONCLUSION
ACKNOWLEDGEMENT
REFERENCES
