[Retracted] Analyzing the Performance of Machine Learning Techniques in Disease Prediction

Table 1

Pros and cons from previous studies

Sl. No.	Authors and methodologies	Pros	Cons
1	Adaptive neuro-fuzzy inference system. Kavitha and Kannan [16]	Enhancing the accuracy and performance	The cost is high when compared with other methods
2	Naive Bayes. Dai et al. [20]	The model applies a specific likelihood of occurrence of the specified task	It is a probability estimation and hence may not be applied for chronic diseases
3	K-nearest neighbour. Ross et al. [26]	One of the most commonly used ML algorithms	There are more advanced models that are currently in place
4	ANN. Kharche et al. [29]	The interconnection can be effectively rewired, and hence it can adapt to the changing environment	The more hidden layers will impact the overall output and interpretation of the data