… Then, Feature extraction is carried out using k-means clustering … of the suggested hybrid
approach for analyzing different … disease prognosis, a recurrent neural network (RNN) along …

… Verma and others [4] proposed a k-means algorithm with … methods and deep learning
methods to predict heart disease. … upon the genetic algorithm and neural networks. They used a …

… as in classification, hence the hybrid approach with the coordination of machine learning …
hybrid heart disease prediction model with K-Means clustering and Artificial Neural Network …

… The hybrid approach's clustering method necessitates the … Data is partitioned into k clusters
using K-means, which … data mining techniques in predicting heart disease," Telematics …

… a hybrid approach to predict heart disease among patients using KMeans and artificial neural
networks. … groups using K-Means. Further, the identified clusters were used as input to the …

… results regarding breast cancer, heart disease and diabetes to … [9] proposed a hybrid approach
implementing K-means for … the decision tree and artificial neural network came out to be …

… or predicting the pattern of pandemic outbreaks, include … In addition, the results revealed
that the K-means algorithm with … In this study, researchers used the K-means clustering method …

… forecasting accuracy of monthly total vehicle sales as the results clearly denote that the hybrid
approach … representation is done by implementing the neural network model [32] and the …

… Similarly, this study [10] proposed a hybrid approach called Bacterial Foraging-PSO (BF-…
method as a training algorithm for Artificial Neural Network (ANN) to prognosticate heart disease…

… in people, many data mining and neural network approaches … This work developed a deep
learning system with a hybrid approach … of the operation of the K-Means clustering technique: …