A Prototype of Doctor Recommendation System using Classification Algorithms
Ashok Bhansali, Naresh Kumar Nagwani · 2021
Doctor recommender system is a very useful and emerging area in data science and health informatics. In recent time many approaches and applications have been proposed in this direction. This paper presents a simple prototype of recommending a doctor using classification based models. In the proposed approach patients’ information and preferences are selected as input to train the model and using classification algorithms a suitable doctor is recommended. In this work probability-based classifier and decision tree-based classifiers are used for recommending a doctor and a comparative study is also presented between them. It is found that ensemble machine learning based classifier Random Forest, performs better than C4.5 and Naïve Bayes classifier.