Health Care & Disease Prediction Webapp Using AI/ML

Authors

  • Akshay Neurgaonkar  Department of Computer Department, Zeal College of Engineering & Research, Pune, Maharashtra, India
  • Tejas Inamdar  Department of Computer Department, Zeal College of Engineering & Research, Pune, Maharashtra, India
  • Ravikant Rathod  Department of Computer Department, Zeal College of Engineering & Research, Pune, Maharashtra, India

Keywords:

Random Forest, Machine Learning, Deep Learning, Disease Prediction

Abstract

Health Care and Disease Prediction Using AI/Machine Learning is an online application that predicts the condition based on information or numeric symptoms given by the patient and gives reliable findings based on the input. If the patients aren't serious and only want to know what kind of ailment they've had. It is a system that provides the user with advice and tactics for maintaining their health as well as disease information utilizing this prediction. In the current era, the health industry plays an important role in curing the disease of the patients, so that is additionally a type of assistance for the health industry to tell the patient, and it is also useful for the patients in case they do not want to go to the hospital or any other clinics, so simply by entering the numerical data of symptoms and all other useful information, the user can get to know the disease they are suffering from, and the health industry can also get the information. This Health Care & Disease Prediction Using Machine Learning is completely done with the help of Machine Learning and Python Programming language with a Website Interface for it and also using the dataset that is available previously by the hospitals using that we will predict the disease.

References

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Published

2022-04-30

Issue

Section

Research Articles

How to Cite

[1]
Akshay Neurgaonkar, Tejas Inamdar, Ravikant Rathod, " Health Care & Disease Prediction Webapp Using AI/ML" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 2, pp.449-453, March-April-2022.