A BERT-based sentence embedding model fine-tuned on the PubMed and MedQuAD datasets. It produces high-quality embeddings for medical text that can be used for semantic search, clustering, and similarity calculations. The model is accessible via the sentence-transformers library and supports standard embedding workflows.
In the Foundation models & chat space, S PubMedBert MedQuAD takes a focused approach. It focuses on computing accurate semantic similarity between medical and clinical sentences. S PubMedBert MedQuAD is an open-source project aimed at healthcare AI developers and researchers. The project is open source (Open Source). S PubMedBert MedQuAD is available on the web, the command line, and API.
TimKond builds and maintains S PubMedBert MedQuAD, and the product first shipped in 2023. Among its 3 catalogued features are Sentence Embeddings, Semantic Similarity, and Medical Domain. It exposes integrations via a public API.
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