Natural language processing: mining adverse drug reactions from medical texts

Junjie Lai; Sophia Zhu; Chuang Wang; Bohan Yin; Yihang Zhou; Haotong Hu; Chunya Ji

doi:10.1117/12.2669576

24 March 2023 Natural language processing: mining adverse drug reactions from medical texts

Junjie Lai, Sophia Zhu, Chuang Wang, Bohan Yin, Yihang Zhou, Haotong Hu, Chunya Ji

Proceedings Volume 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022); 126110S (2023) https://doi.org/10.1117/12.2669576
Event: International Conference on Biological Engineering and Medical Science (ICBioMed2022), 2022, Oxford, United Kingdom

Abstract

Adverse drug reaction detection has always been a medical challenge. However, social media can uncover more information about adverse reactions that go unnoticed than traditional clinical reports. In this work, we focused on a dataset on adverse drug reactions obtained from Twitter. We define this problem as a sentiment classification problem and test the performance of machine learning models, convolutional neural networks (CNN), and recurrent neural networks (RNN) on this problem. Moreover, we try to find the ideal architecture to optimize the performance of the neural network by ablation experiments.

Citation Download Citation

Junjie Lai, Sophia Zhu, Chuang Wang, Bohan Yin, Yihang Zhou, Haotong Hu, and Chunya Ji "Natural language processing: mining adverse drug reactions from medical texts", Proc. SPIE 12611, Second International Conference on Biological Engineering and Medical Science (ICBioMed 2022), 126110S (24 March 2023); https://doi.org/10.1117/12.2669576

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