Artificial intelligence in healthcare text processing: a review applied to named entity recognition

Artificial intelligence in healthcare text processing: a review applied to named entity recognition

ContextTraditional methods such as rule-based systems, word embeddings (e.g. Word2Vec, GloVe) and sequence tagging models such as CRFs and HMMs have difficulty capturing the complex and nuanced context of medical texts, leading to low precision and inflexibility. These methods also struggle with the...

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Main Authors: Samuel Santana de Almeida, Raphael Silva Fontes, Luca Pareja Credidio Freire Alves, Methanias Colaço Júnior, Gleyson José Pinheiro Caldeira Silva, Lyane Ramalho Cortez, Antonio Higor Freire de Morais, Guilherme Medeiros Machado, Hugo Gonçalo Oliveira, Aliete Cunha-Oliveira, João Paulo Queiroz dos Santos, Ricardo Alexsandro de Medeiros Valentim
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Artificial Intelligence
Subjects:
named entity recognition (NER)
health texts
BERT model
advanced language models
ChatGPT
SUS
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2025.1584203/full
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https://www.frontiersin.org/articles/10.3389/frai.2025.1584203/full

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