Article

MedionRep: Medical Ontology Representation using Graph Embedding with Medical Text

2022-03-07

Abstract excerpt

<h4>Background: </h4> Electronic Medical Record (EMR) is an electronic record of a patient’s health information. Nowadays, the importance of EMR analysis is increasing in medical informatics. An EMR is multi-modal data containing medical text and medical concepts. Recent studies attempt to embed either medical text or medical concepts to analyze an EMR partially. However, no type of embedding understands an entire...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 6b756da3-408e-538d-b5ef-5a2181763d70
DOI: 10.21203/rs.3.rs-1419796/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

MedionRep: Medical Ontology Representation using Graph Embedding with Medical TextDOI 10.21203/rs.3.rs-1419796/v1Read

Knowledge Graph Embeddings for ICU readmission predictionSemantic proximity Read

ARCH: Large-scale Knowledge Graph via Aggregated Narrative Codified Health Records AnalysisSemantic proximity Read

RD-Embed: Unified representations of rare-disease knowledge from clinical recordsSemantic proximity Read

A Study into Patient Similarity through Representation Learning from Medical RecordsSemantic proximity Read

Clustering rare diseases within an ontology-enriched knowledge graphSemantic proximity Read

Clustering rare diseases within an ontology-enriched knowledge graph.Semantic proximity Read

A Comparison of Representation Learning Methods for Medical Concepts in MIMIC-IVSemantic proximity Read

ClinVec: Unified Embeddings of Clinical Codes Enable Knowledge-Grounded AI in MedicineSemantic proximity Read

Language-model-based patient embedding using electronic health records facilitates phenotyping, disease forecasting, and progression analysisSemantic proximity Read

Enriching representation learning using 53 million patient notes through human phenotype ontology embedding.Semantic proximity Read

Enriching Representation Learning Using 53 Million Patient Notes through Human Phenotype Ontology EmbeddingSemantic proximity Read

Phe2vec: Automated Disease Phenotyping based on Unsupervised Embeddings from Electronic Health RecordsSemantic proximity Read