Applying Personal Knowledge Graphs to Health
Knowledge graphs that encapsulate personal health information, or personal health knowledge graphs (PHKG), can help enable personalized health care in knowledge-driven systems. In this paper we provide a short survey of existing work surrounding the emerging paradigm of PHKGs and highlight the major challenges that remain. We find that while some preliminary exploration exists on the topic of personal knowledge graphs, development of PHKGs remains under-explored. A range of challenges surrounding the collection, linkage, and maintenance of personal health knowledge remains to be addressed to fully realize PHKGs.
Code (0)
등록된 구현이 없습니다.
Tasks
Knowledge GraphsSimilar Papers 제목 키워드 기반
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs
Clinical predictive models often rely on patients' electronic health records (EHR), but integrating medical knowledge to enhance predictions and decision-making is challenging. This is because personalized predictions re…
Decision MakingGraph Neural NetworkKnowledge GraphsPersonal Health Knowledge Graphs for Patients
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…
Knowledge GraphsPerCaM-Health: Personalized Dynamic Causal Graphs for Healthcare Reasoning
Personalized healthcare decisions require reasoning about how physiological and behavioral variables influence an individual patient over time. Existing temporal causal discovery methods are poorly matched to this settin…
Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications
Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that focuses on individualized patient care by mapping the patient's health information in a holistic and multi-dimensional way. PCKGs i…
Data IntegrationDisease PredictionKnowledge GraphsEmpowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
Social networks are vital for information sharing, especially in the health sector for discussing diseases and treatments. These platforms, however, often feature posts as brief texts, posing challenges for Artificial In…
Knowledge Graph EmbeddingsKnowledge GraphsWord Embeddings