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Towards Instructing Disease-Drug Link Prediction with Social Determinants of Health

Published: 16 December 2024 Publication History

Abstract

In this study, we emphasize the importance of incorporating Social Determinants of Health (SDoH)---such as economic, educational, environmental, and behavioral factors---into personalized medicine. These factors are often overlooked by researchers due to challenges like fragmented knowledge, non-standardized research repositories, and evolving ontologies. Excluding SDoH factors limits the accuracy and effectiveness of disease-drug interaction predictions, which are essential for precision medicine. To overcome these challenges, we introduced the BioSocialNet framework, which integrates SDoH factors into knowledge graph construction and uses Graph Convolutional Networks (GCN) for more accurate predictions. BioSocialNet consists of two key components: (1) construction of a comprehensive knowledge graph that merges biomedical and SDoH data, and (2) deployment of GCNs that model the complex interactions between these factors. We applied this framework to incorporate SDoH data from the MIMIC III dataset into PrimeKG, a comprehensive knowledge graph that includes a wide range of diseases, drugs, and biomedical interactions. We then trained a GCN model on this enriched graph, resulting in a significant improvement in disease-drug linkage prediction accuracy, from 88.05% to 94.08%. This finding underscores the pivotal role of SDoH in enhancing the precision and implications of personalized medicine, providing a clear pathway for more accurate and equitable healthcare interventions.

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cover image ACM Conferences
BCB '24: Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
November 2024
614 pages
ISBN:9798400713026
DOI:10.1145/3698587
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 16 December 2024

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Author Tags

  1. Disease-Drug Linkages
  2. Graph Convolutional Networks
  3. Precision Medicine
  4. PrimeKG
  5. Social Determinants of Health

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