Department of Business Development and Technology

Personalized Recommendation Method for Preventing Elderly People from Cardiovascular Disease Complication Using Integrated Objective Distance

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Supansa Chaising, Mae Fah Luang University
  • ,
  • Ramjee Prasad
  • Punnarumol Temdee, Mae Fah Luang University, Thailand

Nowadays, people are living longer than in the past which leads to dramatically increasing numbers of elderly people in the world’s populations. Correspondingly, the elderly are facing critical health concerns, particularly Cardiovascular Disease (CVD). CVD is recognized as the main cause of death worldwide for the aged people. Consequently, prevention of CVD complication is extremely significant for the elderly. The purpose of this research study is to determine a personalized recommendation to the elderly for preventing themselves from the complication of CVDs. Therefore, the personalized recommendation method using integrated objective distance is proposed in this study. The integrated objective distance is a new measurement for computing the distance score for indicating a personal suggestion effectively. Importantly, the proposed personalized recommendation method provides the potential direction for an individual lifestyle adjustment. An experiment of this study is conducted in the context of hypertension, which is one of the most significant risk factors for developing CVD. Input data is collected from 121 elderly people who have a high risk of CVD in Chiang Rai, Thailand. An experimental result shows that the proposed method can provide efficient suggestions to elderly people when compared to those from human experts with 95% accuracy.

Original languageEnglish
JournalWireless Personal Communications
Pages (from-to)215-233
Number of pages19
Publication statusPublished - Mar 2021

    Research areas

  • Cardiovascular disease (CVD), Elderly people, Integrated objective distance, Personalization, Recommendations

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