Authors :
Akshata Ringe; Tejaswini Shinde; Krushnalata Zurule; Omkar Patil
Volume/Issue :
Volume 8 - 2023, Issue 3 - March
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/425sGMf
DOI :
https://doi.org/10.5281/zenodo.7723079
Abstract :
Evolution of modern technologies like data
science and machine learning has opened the path for
healthcare communities and medical institutions, to
detect the diseases earliest as possible and it helps to
provide better patient care. Accuracy of detecting the
possible diseases is reduced when we do not have
complete medical data. Furthermore, certain diseases
are region-based, which might cause weak disease
prediction. Our body shows the symptoms when
something wrong is happening within our body,
sometime it may be just minor problem but sometimes we
can have severe illness and if we do not take care of these
symptoms at the early stage then it might be too late to
cure the disease. So we are proposing a disease prediction
system that can predict the possible diseases based on
symptoms so it can be cured at the early stage. It saves
time that is required to do the complete diagnosis of the
patient and based on the suggestions provided by the
system we can only get the patient diagnosed for those
diseases that are required. In this paper, we are using
machine learning algorithms that try to accurately
predict possible diseases. The results generated by the
proposed system have an accuracy of up to 87%. The
system has incredible potential in anticipating the
possible diseases more precisely. The main motive of this
study is to help the nontechnical person and freshman
doctors to make a correct opinion about the diseases
Keywords :
Disease Prediction System, Machine Learning, Multilinear Regression (MLR), Support Vector Machine (SVM).
Evolution of modern technologies like data
science and machine learning has opened the path for
healthcare communities and medical institutions, to
detect the diseases earliest as possible and it helps to
provide better patient care. Accuracy of detecting the
possible diseases is reduced when we do not have
complete medical data. Furthermore, certain diseases
are region-based, which might cause weak disease
prediction. Our body shows the symptoms when
something wrong is happening within our body,
sometime it may be just minor problem but sometimes we
can have severe illness and if we do not take care of these
symptoms at the early stage then it might be too late to
cure the disease. So we are proposing a disease prediction
system that can predict the possible diseases based on
symptoms so it can be cured at the early stage. It saves
time that is required to do the complete diagnosis of the
patient and based on the suggestions provided by the
system we can only get the patient diagnosed for those
diseases that are required. In this paper, we are using
machine learning algorithms that try to accurately
predict possible diseases. The results generated by the
proposed system have an accuracy of up to 87%. The
system has incredible potential in anticipating the
possible diseases more precisely. The main motive of this
study is to help the nontechnical person and freshman
doctors to make a correct opinion about the diseases
Keywords :
Disease Prediction System, Machine Learning, Multilinear Regression (MLR), Support Vector Machine (SVM).
