A Novel Method for Identifying Bipolar Disorder Based on Diagnostic Texts
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8462-6_5
Reference20 articles.
1. AbaeiKoupaei, N., Al Osman, H.: A multi-modal stacked ensemble model for bipolar disorder classification. IEEE Trans. Affect. Comput. 14(1), 236–244 (2023)
2. Aich, A., et al.: Towards intelligent clinically-informed language analyses of people with bipolar disorder and schizophrenia. In: Findings of the Association for Computational Linguistics: EMNLP 2022, pp. 2871–2887 (2022)
3. Baki, P., Kaya, H., Çiftçi, E., Güleç, H., Salah, A.A.: A multimodal approach for mania level prediction in bipolar disorder. IEEE Trans. Affect. Comput. 13(4), 2119–2131 (2022)
4. Chang, C.C., Lin, C.J.: Libsvm: a library for support vector machines. ACM Trans. Intell. Syst. Technol. (TIST) 2(3), 1–27 (2011)
5. Cheng, Y., et al.: Hsan-capsule: a novel text classification model. Neurocomputing 489, 521–533 (2022)
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