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Towards Effective Named Entity Recognition in Uzbek Medical Contexts

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Department of Information Technologies

DOI

https://doi.org/10.1109/SIBIRCON63777.2024.10758445
Final published version

Davlatyor B. Mengliev
Vladimir B. Barakhnin
Barno S. Samandarova
Nargiza A. Shamieva
Umida U. Rakhmanova
Bahodir B. Ibragimov

Original language	English
Title of host publication	2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2024
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	294-298
Number of pages	5
ISBN (Print)	9798331532024
DOIs	https://doi.org/10.1109/SIBIRCON63777.2024.10758445
Publication status	Published - 26 Nov 2024
Event	2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences - Новосибирск, Russian Federation Duration: 30 Sept 2024 → 2 Nov 2024

Publication series

Name	2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2024

Conference

Conference	2024 IEEE International Multi-Conference on Engineering, Computer and Information Sciences
Abbreviated title	SIBIRCON 2024
Country/Territory	Russian Federation
City	Новосибирск
Period	30.09.2024 → 02.11.2024

OECD FOS+WOS

1.02 COMPUTER AND INFORMATION SCIENCES

Research areas

Multilingual models, Natural Language Processing, Spacy library, Uzbek medical texts, algorithm efficiency, comparative analysis, custom model training, entity detection accuracy, marked corpus, medical data processing, medical terminology, neural network architectures, text mining

ID: 61788211