• Pranita A Patil
• Seemab Nadaf
• Dr. M.S.Karyakarte
• Prof. Y.V.Dongre

Today’s healthcare industries are moving from volume-based business into value-based business, which requires doctors and nurses to be more efficient. This will improve healthcare industry, life style and provides longer life, which prevent diseases, illness. Data analytics tools are used to improve healthcare in areas like reports, decision making, and prediction and prevention system. Healthcare data is more complex because abundance data is available. Healthcare systems collect large amount of textual and numeric data about patients, visits, prescriptions, physician notes etc. Therefore, in healthcare data analytics tool is important to manage a huge amount of complex data, which is used to improve healthcare industry and provide accuracy and efficiency. Machine Learning in healthcare is used to analyze different type of data and predict possible outcomes, risk prediction, etc. WEKA uses the statistical procedures such as simple linear regression, logistic regression models and machine language techniques like decision trees, clustering, multi-layer perceptron When socioeconomic parameter is combined with patient’s electronic health records, providers will have a more detail view of their patients, allowing them to make better decisions.

Machine learning algorithms, WEKA, Correlation, Linear Regression.

"Applying Machine Learning Algorithms to find correlation between socioeconomic data and diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.560-564, June 2019, Available :http://www.jetir.org/papers/JETIR1906T67.pdf

"Applying Machine Learning Algorithms to find correlation between socioeconomic data and diseases", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp560-564, June 2019, Available at : http://www.jetir.org/papers/JETIR1906T67.pdf