Mining medical academic articles using recurrent neural networks

dc.contributor.advisor	Tomic, Oliver
dc.contributor.advisor	Liland, Kristian Hovde
dc.contributor.author	Radwan, Mohamed
dc.contributor.editor	Radwan, Mohamed
dc.date.accessioned	2021-12-02T14:02:11Z
dc.date.available	2021-12-02T14:02:11Z
dc.date.issued	2021
dc.identifier.uri	https://hdl.handle.net/11250/2832609
dc.description.abstract	In this thesis, we present our methods and results for mining the MedMentions data [Mohan and Li, 2019]. We propose a pipeline for combining mention classification and mention disambiguation. We will use the Long Short Term Memory (LSTM) neural network architecture for mention detection and mention classification. Also we use nearest neighbour search using embeddings in the Unified Medical Language System (UMLS) concepts in order to disambiguate mentions.	en_US
dc.language.iso	eng	en_US
dc.publisher	Norwegian University of Life Sciences, Ås	en_US
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no	*
dc.title	Mining medical academic articles using recurrent neural networks	en_US
dc.type	Master thesis	en_US
dc.description.localcode	M-DV	en_US

Med mindre annet er angitt, så er denne innførselen lisensiert som Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal