Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts

HIGHLIGHTS

• who: Isabel Segura-Bedmar from the 8911, Spain have published the research: Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts, in the Journal: (JOURNAL)
• what: The paper explores several deep learning techniques such as Bidirectional Long Short Term Memory (BiLSTM) networks or deep contextualized word represen‑ tations based on Bidirectional Encoder Representations from Transformers (BERT) to recognize rare diseases and their clinical manifestations (signs and symptoms). The approach proposed by Habibi et_al was one of the first works to exploit pre-trained word embeddings to initialize a BiLSTM+CRF . . .
  

   

  

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