Publications

@article{mazo_ontology-based_2018,

title = {Ontology-based automatic reclassification of tissues and organs in histological images},

author = {Claudia Mazo and Maria Trujillo and Enrique Alegre and Liliana Salazar},

url = {https://ceur-ws.org/Vol-2100/paper9.pdf},

year  = {2018},

date = {2018-01-01},

journal = {Proceedings of the 12th Alberto Mendelzon International Workshop on Foundations of},

volume = {390},

pages = {1–4},

abstract = {Heterogeneous data sources, such as images and human knowledge, require different processing approaches. This paper integrates visual descriptors and an ontology to classify tissues and organs of the human cardiovascular system. A cascade Support Vector Machine (SVM) first classifies images based on texture descriptors, and then results are refined using a histological ontology. This combined approach improves classification accuracy compared to image-based methods alone.},

keywords = {Automatic Classification, histological ontology, Histology Images, image processing},

pubstate = {published},

tppubtype = {article}

}

@article{mazo_histological_2017,

title = {A histological ontology of the human cardiovascular system},

author = {Claudia Mazo and Liliana Salazar and Oscar Corcho and Maria Trujillo and Enrique Alegre},

url = {https://link.springer.com/article/10.1186/s13326-017-0158-5},

year  = {2017},

date = {2017-01-01},

journal = {Journal of biomedical semantics},

volume = {8},

pages = {1–15},

abstract = {introduces a histological ontology of the human cardiovascular system, developed collaboratively by histology experts and computer scientists. The ontology follows a methodology based on Conceptual Models (CMs) and is validated using tools like OOPS!, expert evaluations, and its ability to answer Competency Questions (CQs). The ontology is publicly accessible at BioPortal and W3ID. 

The ontology is designed to support complex applications, including teaching, medical practices, bio-medical research, and natural language interactions.},

note = {Publisher: BioMed Central},

keywords = {bioinformatics, cardiovascular system, histological ontology, medical teaching and research},

pubstate = {published},

tppubtype = {article}

}