A Learning-Based Approach to Combine Medical Annotation Results

Autor:	Cédric Pruski, Silvio Domingos Cardoso, Ying-Chi Lin, Marcos Da Silveira, Anika Groß, Victor Christen, Erhard Rahm
Rok vydání:	2018
Předmět:	0301 basic medicine Open Biomedical Ontologies Set (abstract data type) 03 medical and health sciences Annotation 030104 developmental biology Information retrieval Process (engineering) Computer science media_common.quotation_subject Learning based Quality (business) media_common
Zdroj:	Lecture Notes in Computer Science ISBN: 9783030060152 DILS
Popis:	There exist many tools to annotate mentions of medical entities in documents with concepts from biomedical ontologies. To improve the overall quality of the annotation process, we propose the use of machine learning to combine the results of different annotation tools. We comparatively evaluate the results of the machine-learning based approach with the results of the single tools and a simpler set-based result combination.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::af0a251249693ab91e626cae138a5df2 https://doi.org/10.1007/978-3-030-06016-9_13 Zobrazit plný text záznamu