• Ifra Altaf
• Muheet Ahmed Butt
• Majid Zaman Baba
• S Jahangeer Sidiq

Clinical databases contain information about patients and their health conditions and this information can be used to mine the hidden relationships and patterns present inside the data that helps in providing up-to-the-minute medicinal awareness with assistance in diagnoses and treatment of diseases. Classification and prediction models support medical diagnosis which helps to arrive at the accurate decision-making and actual prediction of different diseases. Many researchers have used various data mining techniques to accurately detect and predict the liver disease and they have diverse views and estimations of confirming their proposed algorithms as better algorithms in predicting and classifying the disease. To find out how data mining and machine learning techniques have developed during the past decade, this paper assesses certain classification algorithms for predicting various liver diseases through a survey of literature from 2010 to 2019.

liver diseases, hepatitis, classification techniques, medical diagnosis, literature review

"A Comparative Study of Various Data Mining Algorithms for effective Liver Disease Diagnosis – A decade review from 2010 to 2019.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 1, page no.980-995, January-2019, Available :http://www.jetir.org/papers/JETIRDY06165.pdf

"A Comparative Study of Various Data Mining Algorithms for effective Liver Disease Diagnosis – A decade review from 2010 to 2019.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 1, page no. pp980-995, January-2019, Available at : http://www.jetir.org/papers/JETIRDY06165.pdf