Personal Health Knowledge Graphs for Patients

TL;DR

This paper reviews the development of personal health knowledge graphs, emphasizing their importance in personalized patient data analytics and discussing the challenges in designing and implementing such systems.

Contribution

It provides a critique of current literature on personal health knowledge graphs and discusses key research challenges in their development and deployment.

Findings

Highlights the need for context-aware patient data integration

Identifies key challenges in PHKG design and operation

Emphasizes the importance of personalized health insights

Abstract

Existing patient data analytics platforms fail to incorporate information that has context, is personal, and topical to patients. For a recommendation system to give a suitable response to a query or to derive meaningful insights from patient data, it should consider personal information about the patient's health history, including but not limited to their preferences, locations, and life choices that are currently applicable to them. In this review paper, we critique existing literature in this space and also discuss the various research challenges that come with designing, building, and operationalizing a personal health knowledge graph (PHKG) for patients.