International journal of advanced smart convergence

The Institute of Internet, Broadcasting and Communication (한국인터넷방송통신학회)
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Prediction of Cognitive Ability Utilizing a Machine Learning approach based on Digital Therapeutics Log Data

  • Yeojin Kim (Department of Computer Science and Engineering, Ewha Womans University) ;
  • Jiseon Yang (Department of Artificial Intelligence) ;
  • Dohyoung Rim (Department of Artificial Intelligence) ;
  • Uran Oh (Department of Computer Science and Engineering, Ewha Womans University)
  • Received : 2023.03.05
  • Accepted : 2023.03.13
  • Published : 2023.06.30
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Abstract

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.

Keywords

Acknowledgement

This work was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government(MSIT) (No. RS-2023-00155966, Artificial Intelligence Convergence Innovation Human Resources Development (Ewha Womans University)), and received research support from Rowan in 2023.

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