In this research, we develop a hybrid recommendation system recommendation system for healthy living programs to patients with chronic diseases. Our experiments indicate that our model compared favorably against other real-world recommendation applications in terms of accuracy. We also demonstrated that the proposed hybrid algorithm performed better than traditional CF in terms of error rate, precision and recall.
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