Determining Important Features in Multidimensional Health Data for Individualized Precision Healthcare

Ruichen Cong, Jianlun Wu, Shoji Nishimura, Atsushi Ogihara, Qun Jin

研究成果: Conference contribution

抄録

In recent years, there has been a growing need for individuals' health management by using sensors and wearable devices to record daily activity and monitor health indicators. A large amount of health data needs to be analyzed to investigate the essential impact factors related to individuals' health and help individuals manage their health. In this paper, we investigate the important features influencing personal health from health data obtained from wearable devices and health data based on Traditional Chinese Medicine (TCM). We focus on investigating and selecting more influential health features and then performing machine learning algorithms for modeling. The results show that daily activity consumption is of a greater influence on wearable device data, and the pulse position that represents the kidney is identified as having the most significant impact on TCM health status among all pulse positions. Moreover, we selected the most influential features to perform the regression model and compared them with all the features. The results show that after feature selection, the Mean Squared Error (MSE) is smaller, and the R-square Score (R2) is greater than before.

本文言語English
ホスト出版物のタイトル2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023
出版社Institute of Electrical and Electronics Engineers Inc.
ページ77-83
ページ数7
ISBN(電子版)9798350304602
DOI
出版ステータスPublished - 2023
イベント2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023 - Abu Dhabi, United Arab Emirates
継続期間: 2023 11月 142023 11月 17

出版物シリーズ

名前2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, International Conference on Pervasive Intelligence and Computing, International Conference on Cloud and Big Data Computing, International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

Conference

Conference2023 IEEE International Conference on Dependable, Autonomic and Secure Computing, 2023 International Conference on Pervasive Intelligence and Computing, 2023 International Conference on Cloud and Big Data Computing, 2023 International Conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023
国/地域United Arab Emirates
CityAbu Dhabi
Period23/11/1423/11/17

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • ハードウェアとアーキテクチャ
  • 情報システム
  • 情報システムおよび情報管理
  • 安全性、リスク、信頼性、品質管理
  • 制御と最適化

フィンガープリント

「Determining Important Features in Multidimensional Health Data for Individualized Precision Healthcare」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル