Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Dementia Prediction Model based on Gradient Boosting

이기종 머신러닝 모델 기반 치매예측 모델

  • Lee, Taein (Psychology & Applied Artifical Intelligence, Sungkyunkwan University) ;
  • Oh, Hayoung (College of Computing and Informatics, Sungkyunkwan University)
  • Received : 2021.06.26
  • Accepted : 2021.10.12
  • Published : 2021.12.31
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Abstract

Machine learning has a close relationship with cognitive psychology and brain science and is developing together. This paper analyzes the OASIS-3 dataset using machine learning techniques and proposes a model for predicting dementia. Dimensional reduction through PCA (Principal Component Analysis) is performed on the data quantifying the volume of each area among OASIS-3 data, and only important elements (features) are extracted and then various machine learning including gradient boosting and stacking Apply the models and compare the performance of each. Unlike previous studies, the proposed technique has a great differentiation because it uses not only the brain biometric data, but also basic information data such as the participant's gender and medical information data of the participant. In addition, it was shown that the proposed technique through various performance evaluations is a model that can better predict dementia by finding features that are more related to dementia among various numerical data.

머신러닝은 인지심리, 뇌과학과 긴밀한 관계를 유지하며 함께 발전하고 있다. 본 논문은 OASIS-3 dataset을 머신러닝 기법을 이용하여 분석하고, 이를 통해 치매를 예측하는 모델을 제안한다. OASIS-3 데이터 중 각 영역의 부피를 수치화한 데이터들에 대해 PCA(Principal component analysis) 를 통한 차원 축소를 실행한 뒤, 중요한 요소(특징)들만 추출 후 이에 대해 그래디언트 부스팅, 스태킹을 포함한 다양한 머신러닝 모델들을 적용, 각각의 성능을 비교한다. 제안하는 기법은 기존 연구들과 달리 뇌 생체 데이터들은 물론 참가자의 성별 등의 기본 정보 데이터, 참여자의 의료 정보 데이터를 사용했기에 차별성이 크다. 또한, 다양한 성능평가를 통해 제안하는 기법이 다양한 수치 데이터 중 치매와 더 많은 관련성을 보이는 특징들을 찾아내어 치매를 더 잘 예측할 수 있는 모델임을 보였다.

Keywords

Acknowledgement

Following are results of a study on the "Convergence and Open Sharing System" Project, supported by the Ministry of Education and National Research Foundation of Korea. Data were provided by OASIS and AV-45 doses were provided by Avid Radiopharmaceuticals, a wholly owned subsidiary of Eli Lilly.

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