Dimas263/NLP_NER_BERT_BILSTM_CRF_Named_Entity_Recognition

NLP Named Entity Recognition dalam bidang Biomedis, mendeteksi teks dan membuat klasifikasi apakah teks tersebut mempunyai entitas plant atau disease, memberi label pada teks, menguji hubungan entitas plant dan disease, menilai kecocokan antara kedua entitas, membandingkan hasil uji dengan menggunakan models BERT-BILSTM-CRF

11
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Experimental

This project helps biomedical researchers and scientists automatically identify and categorize key terms like 'plant' and 'disease' within research texts. You input raw biomedical text, and it outputs the text with specific plant and disease entities highlighted and labeled, alongside their relationships. It's designed for anyone working with large volumes of biomedical literature who needs to quickly extract specific biological entities.

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Use this if you need to automatically extract and label mentions of plants and diseases from biomedical research papers or clinical notes to accelerate your research.

Not ideal if you need to extract entities beyond plants and diseases, or if your text is not related to the biomedical domain.

biomedical-research text-analysis literature-review disease-etiology botany
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 3 / 25
Maturity 8 / 25
Community 0 / 25

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Last pushed

Aug 01, 2022

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