# Personal Health Knowledge Graphs for Patients

arXiv: https://arxiv.org/abs/2004.00071 · HTML: https://mlsanity.com/paper/2004.00071/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2020.

## Built on by (most cited first, 7 of 7)

- [GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs](https://mlsanity.com/paper/2305.12788/) (2023)
- [An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap](https://mlsanity.com/paper/2304.09572/) (2023)
- [Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications](https://mlsanity.com/paper/2402.12608/) (2024)
- [Representation Learning for Person or Entity-centric Knowledge Graphs: An Application in Healthcare](https://mlsanity.com/paper/2305.05640/) (2023)
- [Healthcare Knowledge Graph Construction: State-of-the-art, open issues, and opportunities](https://mlsanity.com/paper/2207.03771/) (2022)
- [CoLoTa: A Dataset for Entity-based Commonsense Reasoning over Long-Tail Knowledge](https://mlsanity.com/paper/2504.14462/) (2025)
- [CommonWhy: A Dataset for Evaluating Entity-Based Causal Commonsense Reasoning in Large Language Models](https://mlsanity.com/paper/2605.12918/) (2026)

## Abstract (arXiv)

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.