AIMC Topic: Semantics

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

Studies in health technology and informatics Aug 22, 2024
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 ...
Signal Transduction Drug-Related Side Effects and Adverse Reactions Humans Semantics Machine Learning Adverse Drug Reaction Reporting Systems Databases, Factual
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Merging Biomedical Ontologies with BioSTransformers.

Studies in health technology and informatics Aug 22, 2024
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...
Unified Medical Language System Semantics Biological Ontologies Humans Neural Networks, Computer
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Pre-Processing of Categorical Features Within Medical Analysis Systems.

Studies in health technology and informatics Aug 22, 2024
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...
Semantics Neoplasms Natural Language Processing Humans Machine Learning Algorithms
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SemOntoMap: A Hybrid Approach for Semantic Annotation of Clinical Texts.

Studies in health technology and informatics Aug 22, 2024
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...
Humans Natural Language Processing Semantics Electronic Health Records Unsupervised Machine Learning
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Semantic Mapping of Named-Entities in openEHR Templates and Ad-hoc Generation of Compositions.

Studies in health technology and informatics Aug 22, 2024
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...
Information Storage and Retrieval Semantics Electronic Health Records Natural Language Processing Humans Software
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OntoBridge Versus Traditional ETL: Enhancing Data Standardization into CDM Formats Using Ontologies Within the DATOS-CAT Project.

Studies in health technology and informatics Aug 22, 2024
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...
Semantics Humans Biological Ontologies Software Electronic Health Records Information Storage and Retrieval
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The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII.

Database : the journal of biological databases and curation Aug 8, 2024
The BioRED track at BioCreative VIII calls for a community effort to identify, semantically categorize, and highlight the novelty factor of the relationships between biomedical entities in unstructured text. Relation extraction is crucial for many bi...
Humans Natural Language Processing Databases, Factual Data Mining Semantics
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Heterogeneous biomedical entity representation learning for gene-disease association prediction.

Briefings in bioinformatics Jul 25, 2024
Understanding the genetic basis of disease is a fundamental aspect of medical research, as genes are the classic units of heredity and play a crucial role in biological function. Identifying associations between genes and diseases is critical for dia...
Algorithms Genetic Predisposition to Disease Genetic Association Studies Computational Biology Neural Networks, Computer Machine Learning Humans Semantics
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High-rate emphasized DeepLabV3Plus for Semantic Segmentation of Breast Cancer-related Hematoxylin and Eosin-stained Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Deep learning algorithms have been successfully adopted to extract meaningful information from digital images, yet many of them have been untapped in the semantic image segmentation of histopathology images. In this paper, we propose a deep convoluti...
Breast Neoplasms Deep Learning Algorithms Hematoxylin Female Image Processing, Computer-Assisted Humans Semantics Staining and Labeling Eosine Yellowish-(YS) Neural Networks, Computer
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Integration of background knowledge for automatic detection of inconsistencies in gene ontology annotation.

Bioinformatics (Oxford, England) Jun 28, 2024
MOTIVATION: Biological background knowledge plays an important role in the manual quality assurance (QA) of biological database records. One such QA task is the detection of inconsistencies in literature-based Gene Ontology Annotation (GOA). This man...
Molecular Sequence Annotation Databases, Genetic Humans Gene Ontology Semantics Computational Biology
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