MedCPT Introduction MedCPT generates embeddings of biomedical texts that can be used for semantic search (dense retrieval) . The model contains two encoders: MedCPT Query Encoder: compute the embeddings of short texts (e.g., questions, search queries, sentences). MedCPT Article Encoder: compute the embeddings of articles (e.g., PubMed titles & abstracts). This repo contains the MedCPT Query Encoder. MedCPT has been pre trained by an unprecedented scale of 255M query article pairs from PubMed search logs , and has been shown to achieve state of the art performance on several zero shot biomedical IR datasets. In general, there are three use cases: 1. Query to article search with both encoders. 2. Query representation for clustering or query to query search with the query encoder. 3. Article representation for clustering or article to article search with the article encoder. For more details, please check out our paper (Bioinformatics, 2023). Please note that the released version is slightly different from the version reported in the paper. Case 1. Using the MedCPT Query Encoder The output will be: These embeddings are also in the same space as those generated by the MedCPT article en…
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