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In the domain of skin related diseases, the variability of semantic features contained within digital skin images is a major barrier to the medical understanding of the symptoms and development of early skin cancers. The desideratum of making these standards machine-readable has led to their formalization in ontologies. In this work, in an attempt to enhance an existing Core Ontology for skin lesion images, hand-coded from image features, high quality images were analyzed by an autonomous ontology creation engine. We show that by exploiting agglomerative clustering methods with distance criteria upon the existing ontological structure, the original domain model could be enhanced with new instances, attributes and even relations, thus allowing for better classification and retrieval of skin lesion categories from the web.<\/jats:p>","DOI":"10.1177\/1460458211405009","type":"journal-article","created":{"date-parts":[[2011,6,28]],"date-time":"2011-06-28T11:24:11Z","timestamp":1309260251000},"page":"140-157","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["A medical ontology for intelligent web-based skin lesions image retrieval"],"prefix":"10.1177","volume":"17","author":[{"given":"Manolis","family":"Maragoudakis","sequence":"first","affiliation":[{"name":"University of the Aegean, Samos, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ilias","family":"Maglogiannis","sequence":"additional","affiliation":[{"name":"University of Central Greece, Lamia, Greece"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2011,6,28]]},"reference":[{"key":"bibr1-1460458211405009","first-page":"29","author":"Berners-Lee T","year":"2001","journal-title":"Scientific American"},{"key":"bibr2-1460458211405009","unstructured":"Marakakis E, Vassilakis K, Kalivianakis E, Micheloyiannis S. 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