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Published Paper Details:
Paper Title
Symptoms Based Disease Diagnosis Using Machine Learning
Authors
Vasavi Sravanthi Balusa
Keywords
Machine Learning, Disease, Symptoms, Efficiency, Supervised, Accuracy
Abstract
Now a days, people face various diseases due to environmental condition and their living habits. So the prediction of disease at an earlier stage becomes an important task. The correct prediction of disease is the most challenging task. To overcome this problem Machine Learning plays an important role to predict the disease. Medical science has a large amount of data growth per year. Due to the increasing amount of data growth in the medical and healthcare field the accurate analysis of medical data has been benefits from early patient care. With the help of disease data, machine learning finds hidden pattern information in a huge amount of medical data. With the help of disease symptoms data set disease prediction is done by using Machine learning algorithms like Random forest and Support Vector Machine.
IJCRT's Publication Details
Unique Identification Number - IJCRT2407974
Paper ID - 266846
Page Number(s) - i701-i706
Pubished in - Volume 12 | Issue 7 | July 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Vasavi Sravanthi Balusa, "Symptoms Based Disease Diagnosis Using Machine Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 7, pp.i701-i706, July 2024, Available at :http://www.ijcrt.org/papers/IJCRT2407974.pdf
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Volume 14 | Issue 3
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Last Date :
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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