An Overview of Recommendation Techniques and Their Applications in Healthcare

• 作 者: Wenbin Yue Zidong Wang Jieyu Zhang Xiaohui Liu
• 机 构: Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB83PH, United Kingdo
• 出 处: 自动化学报（英文版）
• 发表日期: 2021年4期
• 关键词: Collaborative filtering (CF) content-based recom-mendation healthcare recommenda

With the increasing amount of information on the internet, recommendation system (RS) has been utilized in a variety of fields as an efficient tool to overcome information overload. In recent years, the application of RS for health has become a growing research topic due to its tremendous advantages in providing appropriate recommendations and helping people make the right decisions relating to their health. This paper aims at presenting a comprehensive review of typical recommendation techniques and their applications in the field of healthcare. More concretely, an overview is provided on three famous recommendation techniques, namely, content-based, collaborative filtering (CF)-based, and hybrid methods. Next, we provide a snapshot of five application scenarios about health RS, which are dietary recommendation, lifestyle recommendation, training recommendation, decision-making for patients and physicians, and disease-related prediction. Finally, some key challenges are given with clear justifications to this new and booming field.