mlsanityData to 14 Oct 2026

Using a Personal Health Library-Enabled mHealth Recommender System for Self-Management of Diabetes Among Underserved Populations: Use Case for Knowledge Graphs and Linked Data

arXiv 2103.09311 ↗First posted 16 Mar 2021cs.AI cs.DLcited by 6

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Abstract (arXiv)

Personal health libraries (PHLs) provide a single point of secure access to patients digital health data and enable the integration of knowledge stored in their digital health profiles with other sources of global knowledge. PHLs can help empower caregivers and health care providers to make informed decisions about patients health by understanding medical events in the context of their lives. This paper reports the implementation of a mobile health digital intervention that incorporates both digital health data stored in patients PHLs and other sources of contextual knowledge to deliver tailored recommendations for improving self-care behaviors in diabetic adults. We conducted a thematic assessment of patient functional and nonfunctional requirements that are missing from current EHRs based on evidence from the literature. We used the results to identify the technologies needed to address those requirements. We describe the technological infrastructures used to construct, manage, and integrate the types of knowledge stored in the PHL. We leverage the Social Linked Data (Solid) platform to design a fully decentralized and privacy-aware platform that supports interoperability and care integration. We provided an initial prototype design of a PHL and drafted a use case scenario that involves four actors to demonstrate how the proposed prototype can be used to address user requirements, including the construction and management of the PHL and its utilization for developing a mobile app that queries the knowledge stored and integrated into the PHL in a private and fully decentralized manner to provide better recommendations. The proposed PHL helps patients and their caregivers take a central role in making decisions regarding their health and equips their health care providers with informatics tools that support the collection and interpretation of the collected knowledge.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 6 of its 47 references that are in the map. First posted on arXiv 16 Mar 2021.

Builds on

6 of 47 references.

References · 6

  1. 2020Explainable Artificial Intelligence Recommendation System by Leveraging the Semantics of Adverse Childhood Experiences: Proof-of-Concept Prototype Developmentcited by 4
  2. 2019Making Study Populations Visible through Knowledge Graphscited by 3
  3. 2018Knowledge Integration for Disease Characterization: A Breast Cancer Examplecited by 2
  4. 2016A Web API ecosystem through feature-based reusecited by 1
  5. 2019An Innovative Approach to Addressing Childhood Obesity: A Knowledge-Based Infrastructure for Supporting Multi-Stakeholder Partnership Decision-Making in Quebec, Canadacited by 1
  6. 2019Geo-clustered chronic affinity: pathways from socio-economic disadvantages to health disparitiescited by 1

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Citing papers per year: 2022: 2; 2023: 4.

6 papers.