To Recommend the Best Hospital in an Area Using Machine Learning: Medic Aid Analysis

Authors

  • Siddhant Navele Student, Department of Information Technology, MIT ADT University, Pune, India
  • Rucha Ambale Student, Department of Information Technology, MIT ADT University, Pune, India
  • Varun Kapse Student, Department of Information Technology, MIT ADT University, Pune, India
  • Suyash Ghadge Student, Department of Information Technology, MIT ADT University, Pune, India

Keywords:

Weighted average method, K-nearest neighbour (KNN), Collaborative filtering, Sentiment analysis

Abstract

In the health-care industry, there is a huge demand for the finest Medicare for patients. Weighted average Method approach is used to predict the best hospital for the patient on the basis of various attributes used in the dataset. Health care in India is not easily available, according to various polls conducted over the last decade. Health-care apps now accessible do not enable one-stop access to surrounding hospitals and testing centres. This app's goal is to improve one's health and, as a result, one's quality of life. If people have improved access to healthcare, many chronic diseases can be diagnosed earlier. The goal of this project is to demonstrate how a weighted average technique with content-based filtering may be used in a hospital recommender system and to compare performance. The results reveal that the weighted hybrid technique used in this study does not significantly improve performance, but it does help to provide a prediction score for unrated hospitals that cannot be recommended using simply content-based filtering.

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Published

29-04-2022

How to Cite

[1]
S. Navele, R. Ambale, V. Kapse, and S. Ghadge, “To Recommend the Best Hospital in an Area Using Machine Learning: Medic Aid Analysis”, IJRESM, vol. 5, no. 4, pp. 156–158, Apr. 2022.

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Articles