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1 Ergebnisse
1
Assessing Conventional and Deep Learning-Based Approaches f..:
, In:
2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)
,
Bogacsovics, Gergo
;
Harangi, Balazs
;
Beregi-Kovacs, Marcell
... - p. 000077-000082 , 2024
Link:
https://doi.org/10.1109/SAMI60510.2024.10432795
RT T1 <cTitle>2024 IEEE 22nd World Symposium on Applied Machine Intelligence and Informatics (SAMI)</cTitle>: T1 <Title>Assessing Conventional and Deep Learning-Based Approaches for Named Entity Recognition in Unstructured Hungarian Medical Reports</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10432795&Exemplar=1&LAN=DE A1 Bogacsovics, Gergo A1 Harangi, Balazs A1 Beregi-Kovacs, Marcell A1 Kupas, David A1 Lakatos, Robert A1 Serban, Norbert Daniel A1 Tiba, Attila A1 Toth, Janos YR 2024 SN 2767-9438 K1 Recurrent neural networks K1 Predictive models K1 Transformers K1 Data models K1 Task analysis K1 Positron emission tomography K1 Standards K1 named entity recognition K1 medical-text record K1 natural language processing K1 deep-learning SP 000077 OP 000082 LK http://dx.doi.org/https://doi.org/10.1109/SAMI60510.2024.10432795 DO https://doi.org/10.1109/SAMI60510.2024.10432795 SF ELIB - SuUB Bremen
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