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Drug Drug Interaction Extraction On Ddi

Métriques

F1

Micro F1

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	F1	Micro F1	Paper Title	Repository
Feature-based SVM	0.670	67.0	Extracting drug–drug interactions from literature using a rich feature-based linear kernel approach	-
MOL+CNN	0.7255	72.55	Enhancing Drug-Drug Interaction Extraction from Texts by Molecular Structure Information	-
PubMedBERT	0.8236	82.36	Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing
BioBERT	0.8088	80.88	BioBERT: a pre-trained biomedical language representation model for biomedical text mining
DESC+MOL+SciBERT	0.8408	84.08	Using Drug Descriptions and Molecular Structures for Drug-Drug Interaction Extraction from Literature
CharacterBERT (base, medical)	-	80.38	CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters
Hierarchy Bi-LSTMs +Att.+SDP	0.729	72.9	Drug–drug interaction extraction via hierarchical RNNs on sequence and shortest dependency paths	-
SciFive-large	0.8367	83.67	SciFive: a text-to-text transformer model for biomedical literature
ELECTRAMed	-	79.13	ELECTRAMed: a new pre-trained language representation model for biomedical NLP
Graph Kernel-based method	0.684	68.4	A graph kernel based on context vectors for extracting drug–drug interactions	-

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