AID4HAI: Automatic Idea Detection for Healthcare-Associated Infections from Twitter, a Framework Based on Active Learning and Transfer Learning

Author:

Kharazian Zahra,Rahat Mahmoud,Gama Fábio,Mashhadi Peyman Sheikholharam,Nowaczyk Sławomir,Lindgren Tony,Magnússon Sindri

Publisher

Springer Nature Switzerland

Reference22 articles.

1. Barata, R., Leite, M., Pacheco, R., Sampaio, M.O., Ascensão, J.T., Bizarro, P.: Active learning for imbalanced data under cold start. In: Proceedings of the Second ACM International Conference on AI in Finance, pp. 1–9 (2021)

2. Chen, Y., Mani, S.: Active learning for unbalanced data in the challenge with multiple models and biasing. In: Active Learning and Experimental Design Workshop in Conjunction with AISTATS 2010, pp. 113–126. JMLR Workshop and Conference Proceedings (2011)

3. Christensen, K., et al.: Mining online community data: the nature of ideas in online communities. Food Qual. Prefer. 62, 246–256 (2017)

4. Christensen, K., et al.: How good are ideas identified by an automatic idea detection system? Creativity Innov. Manage. 27(1), 23–31 (2018)

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: Bert: pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)

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