PHKG 2020: Workshop on
The Personal Health Knowledge Graph

THE KNOWLEDGE GRAPH CONFERENCE 2020

9AM - 5PM. Online. May 5, 2020

Introduction

Electronic health records (EHRs) have become a popular source of observational health data for learning insights that could inform the treatment of acute medical conditions. Their utility for learning insights for informing preventive care and management of chronic conditions however, has remain limited. For this reason, the addition of social determinants of health (SDoH) [1] and ‘observations of daily living’ (ODLs) [2] to the EHR have been proposed. This combination of medical, social, behavioral and lifestyle information about the patient is essential for allowing medical events to be understood in the context of one’s life and conversely, allowing lifestyle choices to be considered jointly with one’s medical context; it would be generated by both patients and their providers and potentially useful to both for decision-making. We propose that the personal health knowledge graph is a semantic representation of a patient’s combined medical records, SDoH and ODLs. While there are some initial efforts to clarify what personal knowledge graphs are [3] and how they may be made specific for health [4, 5], there is still much to be determined with respect to how to operationalize and apply such a knowledge graph in life and in clinical practice. There are challenges in collecting, managing, integrating, and analyzing the data required to populate the knowledge graph, and subsequently in maintaining, reasoning over, and sharing aspects of the knowledge graph. Importantly, we recognize that it would not be fruitful to design a universal personal health knowledge graph, but rather, to be use-case driven. In this workshop, we aim to gather health practitioners, health informaticists, knowledge engineers, and computer scientists working on defining, building, consuming, and integrating personal health knowledge graphs to discuss the challenges and opportunities in this nascent space.


[1] Crews DC Ross D Adler N Diez Roux AV, Katz M. Social and behavioral information in electronichealth records: New opportunities for medicine and public health.American Journal of PreventiveMedicine, 49:980–3, 2015.
[2] Uba Backonja, Katherine Kim, Gail R Casper, Timothy Patton,Edmond Ramly, and Patricia FlatleyBrennan. Observations of daily living: putting the “personal” in personal health records.AmericanMedical Informatics Association, 2012, 2012.
[3] Krisztian Balog and Tom Kenter. Personal knowledge graphs: A research agenda. InProceedings ofthe 2019 ACM SIGIR International Conference on Theory of Information Retrieval, pages 217–220, 2019
[4] Amelie Gyrard, Manas Gaur, Saeedeh Shekarpour, Krishnaprasad Thirunarayan, and Amit Sheth.Personalized health knowledge graph. http://knoesis.org/sites/default/files/personalized-asthma-obesity,20(2814):29, 2018.
[5] Tania Bailoni, Mauro Dragoni, Claudio Eccher, Marco Guerini, and Rosa Maimone. Perkapp: Acontext aware motivational system for healthier lifestyles. In2016 IEEE International Smart CitiesConference (ISC2), pages 1–4. IEEE, 2016

Topics

Applications of personal health knowledge graphs

Real-world use cases

Perspectives on personal health

Adaptively contextualizing personal health knowledge graphs

Ensuring privacy and security for a personal health knowledge graph




Models to encode the relevant information in a personal health knowledge graph

Interoperability aspects when integrating personal health data from disparate sources

Reasoning and querying over a personal health knowledge graph

Techniques for keeping personal health knowledge graphs current

Important Dates

(all deadlines are midnight AoE)

Mar 30, 2020

Abstracts due

Apr 17, 2020

Acceptance notifications

May 4, 2020

Camera-ready abstracts due

May 5, 2020

Workshop date

Organizers

Ching-Hua Chen

IBM
Research

Amar Das

IBM
Research

Ying Ding

University of Texas

Deborah McGuinness

Rensselaer

Oshani Seneviratne

Rensselaer

Mohammed Zaki

Rensselaer

Program Committee

Chen Bin (Michigan State University)

Shruthi Chari (Rensselaer)

James Codella (IBM)

Morgan Foreman (IBM)

Dan Gruen (IBM)

Jon Harris (Rensselaer)

Jim McCusker (Rensselaer)





Sabbir Rashid (Rensselaer)

Nidhi Rastogi (Rensselaer)

Justin Rousseau (Dell Med, UT Austin)

Abhik Seal (Abbvie)

Juan Sequeda (data.world)

Sola Shirai (Rensselaer)

Hongyu Wang (UT Austin)

PHKG Discussion Group