Sentence Embeddings For Biomedical Texts

Sentence Embeddings for Biomedical Texts is a technique that converts texts in the biomedical field into high-dimensional vector representations, aiming to capture semantic information and contextual relationships within the texts. This technology generates vectors that reflect the complex associations between biomedical entities and concepts through pre-trained models or fine-tuning for specific tasks, thereby improving the accuracy and efficiency of tasks such as information retrieval, document classification, and knowledge graph construction. These embedding vectors not only support semantic similarity calculations across documents but also facilitate deep mining and intelligent analysis of biomedical data.