2 code implementations • 1 Sep 2021 • Isabel Segura-Bedmar, David Camino-Perdonas, Sara Guerrero-Aspizua
The paper explores the use of several deep learning techniques such as Bidirectional Long Short Term Memory (BiLSTM) networks or deep contextualized word representations based on Bidirectional Encoder Representations from Transformers (BERT) to recognize rare diseases and their clinical manifestations (signs and symptoms) in the RareDis corpus.
3 code implementations • 2 Aug 2021 • Claudia Martínez-deMiguel, Isabel Segura-Bedmar, Esteban Chacón-Solano, Sara Guerrero-Aspizua
The RareDis corpus contains more than 5, 000 rare diseases and almost 6, 000 clinical manifestations are annotated.
