MiNER: Fine-Tuned Biomedical Natural Language Processing for Malaria Disease Entity Recognition in Clinical Texts
The proposed methodology selects and preprocesses a large corpus of scientific articles on malaria, and then annotates them with entities of clinical significance, and leverages BioBERT, a state-of-the-art pre-trained language model, to encode the textual data into context-aware representations.
V. Anoop, N. Devika
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