Research Publications for Vithya Yogarajan
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Yogarajan, V., Montiel, J., Smith, T., & Pfahringer, B. (2022). Predicting COVID-19 patient shielding: A comprehensive study. In Proc 34th Australasian Joint Conference on Advances in Artificial Intelligence (AI 2021) LNCS 13151 (pp. 332-343). Sydney, Australia: Springer International Publishing. doi:10.1007/978-3-030-97546-3_27
Yogarajan, V., Montiel, J., Smith, T., & Pfahringer, B. (2021). Transformers for multi-label classification of medical text: an empirical comparison. In A. Tucker, P. Henriques Abreu, J. Cardoso, P. Pereira Rodrigues, & D. Riaño (Eds.), Proc 19th International Conference on Artificial Intelligence in Medicine (AIME 2021), LNCS 12721 (pp. 114-123). Virtual Event: Springer. doi:10.1007/978-3-030-77211-6_12
Open Access version at:
https://hdl.handle.net/10289/14934
Other publications by:
MONTIEL LOPEZ, Jacob :: YOGARAJAN, Vithya :: SMITH, Anthony C (Tony) :: PFAHRINGER, Bernhard MYogarajan, V., Pfahringer, B., Smith, T., & Montiel, J. (2021). Improving Predictions of Tail-end Labels using Concatenated BioMed-Transformers for Long Medical Documents. arXiv:. Retrieved from http://arxiv.org/abs/2112.01718v1
Yogarajan, V., Pfahringer, B., & Mayo, M. (2020). A review of automatic end-to-end de-Identification: Is high accuracy the only metric?. Applied Artificial Intelligence, 34(3), 251-269. doi:10.1080/08839514.2020.1718343
Yogarajan, V., Montiel, J., Smith, T., & Pfahringer, B. (2020). Seeing the whole patient: Using multi-label medical text classification techniques to enhance predictions of medical codes.. CoRR, abs/2004.00430.
Yogarajan, V., Gouk, H., Smith, T., Mayo, M., & Pfahringer, B. (2020). Comparing high dimensional word embeddings trained on medical text to bag-of-words for predicting medical codes. In P. Sitek, M. Petranik, M. Krótkiewicz, & C. Srinilta (Eds.), Proc 12th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2020) LNCS 12033 (pp. 97-108). Phuket, Thailand: Springer. doi:10.1007/978-3-030-41964-6_9
Open Access version at:
https://hdl.handle.net/10289/13591
Other publications by:
YOGARAJAN, Vithya :: SMITH, Anthony C (Tony) :: MAYO, Michael J :: PFAHRINGER, Bernhard MYogarajan, V., & Ragupathy, R. (2019). Research using electronic health records: not all de-identified datasets are created equal. Journal of Primary Health Care, 11(1), 14-15. doi:10.1071/hc19010
Mayo, M., & Yogarajan, V. (2019). A nearest neighbour-based analysis to identify patients from continuous glucose monitor data. In N. T. Nguyen, F. L. Gaol, T. P. Hong, & B. Trawinski (Eds.), Intelligent Information and Database Systems. ACIIDS 2019. Lecture Notes in Computer Science Vol. 11432 (pp. 349-360). Cham: Springer. doi:10.1007/978-3-030-14802-7_30
Ragupathy, R., Yogarajan, V., & Luoni, C. (2019). Health information research privacy standards should include Māori perspectives on privacy. New Zealand Medical Journal, 132(1494), 64-67.
Yogarajan, V., Pfahringer, B., & Mayo, M. (2019). Automatic end-to-end De-identification: Is high accuracy the only metric?. CoRR, abs/1901.10583.
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