Patient-Centered Healthcare: A Framework for Analyzing Patient Feedback Through Sentiment Analysis and Topic Modeling
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Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63851-0_10
Reference13 articles.
1. Alexander, G., Bahja, M., Butt, G.F., et al.: Automating large-scale health careservice feedback analysis: Sentiment analysis and topic modeling study. JMIR Med. Inform. 10(4), e29385 (2022). https://doi.org/10.2196/29385
2. Altundogan, T.G., Karakose, M., Yılmazer, S., Hanoğlu, E., Demirel, S.: Sentiment analysis for patient reviews in hospitals by CNN and LSTM neural networks using pretrained word embeddings. In: 2023 Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE (2023). https://doi.org/10.1109/ASYU58738.2023.10296829
3. Bozuyla, M.: Sentiment analysis of Turkish drug reviews with bidirectional encoder representations from transformers. ACM Trans. Asian Low-Resour. Lang. Inf. Process. 23(1), 1–17 (2024). https://doi.org/10.1145/3626523
4. Krishnan, A.: Exploring the power of topic modeling techniques in analyzing customer reviews: a comparative analysis. arXiv preprint arXiv:2308.11520 (2023). https://doi.org/10.48550/arXiv.2308.11520
5. Kumar, A., Shekhar, S.: Hybrid model of unsupervised and supervised learning for multiclass sentiment analysis based on users’ reviews on healthcare web forums. J. Artif. Intell. 7(4) (2024). https://doi.org/10.32629/jai.v7i4.971
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