Abstract:

Abstract The Healthcare system is the most essential and intersecting research field. Implementing effective technology in the healthcare system is a boon for the human community. Recently, the need for medical advancement has turned huge attention to healthcare practices. Healthcare practices mainly require healthcare data that comprises patient data, treatment data, and resource management data-daily, the amount of healthcare data increases, making the accuracy and classification more complex. Data mining is the most superior technology for handling those healthcare data effectively. This paper proposes an artificial intelligence with a J48 classification algorithm. This proposed mechanism works intelligently in discovering the hidden patterns of the data and enhances classification accuracy. It is applicable for handling various disease datasets, which include heart diseases, diabetes data, etc. The result from the proposed mechanism improves the accuracy of disease prediction, like whether the disease impacts the patient or not. The comparison proves the proposed system's accuracy efficiency is carried out with random forest, naive Bayes, and k-means. The performance factors for comparison are correctly classified instances, accuracy, sensitivity, and specificity. The simulation outcome shows that the proposed J48 is more efficient in achieving the diagnosis accuracy than the others.

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