# Knowledge Representation and Management: 2023 Highlights and the Rise of Knowledge Graph Embeddings

## TL;DR

This paper summarizes top 2023 research in knowledge representation and management, highlighting the growing importance of knowledge graph embeddings in biomedical applications.

## Contribution

The paper identifies and highlights the most impactful 2023 KRM research, emphasizing the novel use of knowledge graph embeddings in biomedicine.

## Key findings

- Fifteen candidate papers were identified from 1,666 PubMed publications.
- Three best papers focused on knowledge graphs, interoperability, and ontologies.
- Knowledge graph embeddings showed promise in predicting ICU readmissions and measuring disease distances.

## Abstract

Objectives
: We aim to identify, select, and summarize the best papers published in 2023 for the Knowledge Representation and Management (KRM) section of the International Medical Informatics Association (IMIA) Yearbook.

Methods
: We performed PubMed queries and adhered to the IMIA Yearbook guidelines for conducting biomedical informatics literature review to select the best papers in KRM published in 2023.

Results
: Our search yielded a total of 1,666 publications from PubMed. From these, we identified 15 papers as potential candidates for the best papers, and three of them were finally selected as the best papers in the KRM section. The candidate best papers covered three main topics: knowledge graph, knowledge interoperability, and ontology. Notably, two of the three selected best papers explored the potential of knowledge graph embeddings for predicting intensive care unit readmissions and measuring disease distances, respectively.

Conclusions
: The selection process for the best papers in the KRM section for 2023 showcased a wide spectrum of topics, with knowledge graph embeddings emerging as a promising area for supporting machine learning applications in biomedicine.