| pharm-relation-extraction | |
| === | |
| Model trained a model to recognize 4 types of relationships between significant pharmacological entities in russian-language reviews: ADR–Drugname, Drugname–Diseasename, Drugname–SourceInfoDrug, Diseasename–Indication. The input of the model is a review text and a pair of entities, between which it is required to determine the fact of a relationship and one of the 4 types of relationship, listed above. | |
| Data | |
| ---- | |
| Proposed model is trained on a subset of 908 reviews of the [Russian Drug Review Corpus (RDRS)](https://arxiv.org/pdf/2105.00059.pdf). The subset contains the markup of the following types of entities: and contains pairs of entities marked with the 4 listed types of relationships: | |
| - ADR-Drugname — the relationship between the drug and its side effects | |
| - Drugname-SourceInfodrug — the relationship between the medication and the source of information about it (e.g., “was advised at the pharmacy”, e.g., “was advised at the pharmacy”, “the doctor recommended it”); | |
| - Drugname-Diseasname — the relationship between the drug and the disease | |
| - Diseasename-Indication — the connection between the illness and its symptoms (e.g., “cough”, “fever 39 degrees”) | |
| Also, this subset contains pairs of the same entity types between which there is no relationship: for example, a drug and an unrelated side effect that appeared after taking another drug; in other words, this side effect is related to another drug. | |
| Model topology and training | |
| ---- | |
| Proposed model is based on the [XLM-RoBERTA-large](https://arxiv.org/abs/1911.02116) topology. After the additional training as a language model on corpus of unmarked drug reviews, this model was trained as a classification model on 80% of the texts from subset of the corps described above. | |
| How to use | |
| ---- | |
| See section "How to use" in [our git repository for the model](https://github.com/sag111/Relation_Extraction) | |
| Results | |
| ---- | |
| Here are the accuracy, estimated by the f1 score metric for the recognition of relationships on the best fold. | |
| | ADR–Drugname | Drugname–Diseasename | Drugname–SourceInfoDrug | Diseasename–Indication | | |
| | ------------- | -------------------- | ----------------------- | ---------------------- | | |
| | 0.955 | 0.892 | 0.922 | 0.891 | |