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Hospital recommender system

Authors: Shrey Sumariya; Shreyas Rami Rami; Shubham Revadekar; Vidhan Shah; Sudhir Bagul;

Hospital recommender system

Abstract

Elderly patients require more medical effort. It is clear that early-stage disease diagnosis can support time lyand appropriate treatment. But if you don’t pay attention in a timely manner, it can lead to different kinds of health problems that can lead to death. Take advantage of our recommendation system to recommend hospitals. A recommender system uses algorithms to provide product or service recommendations to users. By combining blockchain technology and machine learning models, we provide users with highly accurate recommendations. This whitepaper describes how sophisticated machine learning models and blockchain can be connected to improve recommendations, providing hospitals with higher performance and more accurate recommendations. An optimized model for recommending hospitals in a better manner is the main goal behind this paper.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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