Identifying diseases symptoms and general rules using supervised and unsupervised machine learning
Author:
Funder
University of Torbat Heydarieh
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-69029-8.pdf
Reference34 articles.
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2. Manikandan, K. Diagnosis of diabetes diseases using optimized fuzzy rule set by grey wolf optimization. Pattern Recogn. Lett. 125, 432–438. https://doi.org/10.1016/j.patrec.2023.03.011 (2019).
3. Bajwa, J., Munir, U., Nori, A. & Williams, B. Artificial intelligence in healthcare: Transforming the practice of medicine. Future Healthc. J. 8, 188–194. https://doi.org/10.7861/fhj.2021-0095 (2021).
4. Ahsan, M. M., Luna, S. A. & Siddique, Z. Machine-learning-based disease diagnosis: A comprehensive review. Healthcare 10, 541. https://doi.org/10.3390/healthcare10030541 (2022).
5. Ali, O. et al. A systematic literature review of artificial intelligence in the healthcare sector: Benefits, challenges, methodologies, and functionalities. J. Innov. Knowl. 8, 100333. https://doi.org/10.1016/j.jik.2023.100333 (2023).
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