AI Medical Compendium Topic:
Semantics

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CACER: Clinical concept Annotations for Cancer Events and Relations.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationship between cancer drugs and their associated symptom burden...

Building a Natural Language Interface for FHIR Clinical Terminology Server.

Studies in health technology and informatics
While Fast Healthcare Interoperability Resources (FHIR) clinical terminology server enables quick and easy search and retrieval of coded medical data, it still has some drawbacks. When searching, any typographical errors, variations in word forms, or...

Triangulating evidence in health sciences with Annotated Semantic Queries.

Bioinformatics (Oxford, England)
MOTIVATION: Integrating information from data sources representing different study designs has the potential to strengthen evidence in population health research. However, this concept of evidence "triangulation" presents a number of challenges for s...

BioLORD-2023: semantic textual representations fusing large language models and clinical knowledge graph insights.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: In this study, we investigate the potential of large language models (LLMs) to complement biomedical knowledge graphs in the training of semantic models for the biomedical and clinical domains.

Machine Learning upon RDF Knowledge Graphs for Drug Safety: A Case Study on Reactome Data.

Studies in health technology and informatics
Artificial Intelligence (AI), particularly Machine Learning (ML), has gained attention for its potential in various domains. However, approaches integrating symbolic AI with ML on Knowledge Graphs have not gained significant focus yet. We argue that ...

Merging Biomedical Ontologies with BioSTransformers.

Studies in health technology and informatics
Ontologies play a key role in representing and structuring domain knowledge. In the biomedical domain, the need for this type of representation is crucial for structuring, coding, and retrieving data. However, available ontologies do not encompass al...

Pre-Processing of Categorical Features Within Medical Analysis Systems.

Studies in health technology and informatics
The complexity of the cancer problem domain presents challenges not only to the medical analysis systems tasked with its analysis, but also to the users of such systems. While it is desirable to assist users in operating these medical analysis system...

SemOntoMap: A Hybrid Approach for Semantic Annotation of Clinical Texts.

Studies in health technology and informatics
This study addresses the challenge of leveraging free-text descriptions in Electronic Health Records (EHR) for clinical research and healthcare improvement. Despite the potential of this data, its direct interpretation by computers is limited. Semant...

Semantic Mapping of Named-Entities in openEHR Templates and Ad-hoc Generation of Compositions.

Studies in health technology and informatics
Integration of free texts from reports written by physicians to an interoperable standard is important for improving patient-centric care and research in the medical domain. In the context of unstructured clinical data, NLP Information Extraction ser...

OntoBridge Versus Traditional ETL: Enhancing Data Standardization into CDM Formats Using Ontologies Within the DATOS-CAT Project.

Studies in health technology and informatics
Common Data Models (CDMs) enhance data exchange and integration across diverse sources, preserving semantics and context. Transforming local data into CDMs is typically cumbersome and resource-intensive, with limited reusability. This article compare...