Identifying causal relations in tweets using deep learning: Use case on diabetes-related tweets from 2017-2021

1 code implementation • 1 Nov 2021 • Adrian Ahne, Vivek Khetan, Xavier Tannier, Md Imbessat Hassan Rizvi, Thomas Czernichow, Francisco Orchard, Charline Bour, Andrew Fano, Guy Fagherazzi

A cause-effect-tweet dataset was manually labeled and used to train 1) a fine-tuned Bertweet model to detect causal sentences containing a causal association 2) a CRF model with BERT based features to extract possible cause-effect associations.

Deep clustering of longitudinal data

no code implementations • 9 Feb 2018 • Louis Falissard, Guy Fagherazzi, Newton Howard, Bruno Falissard

These methods provide a framework to model complex, non-linear interactions in large datasets, and are naturally suited to the analysis of hierarchical data such as, for instance, longitudinal data with the use of recurrent neural networks.

Clustering Deep Clustering +1