… We used K-means clustering, feature extraction and selection with PSO, and correlation…
hybrid approach using genetic algorithms and artificial neural networks to forecast cardiac illness …

… heart disease and to predict classes of people who will develop diabetes in the future
using a combined dataset and another hybrid … , neural networks, and NLP. He can be contacted …

… hybrid method based on principal component analysis, fuzzy c-means and ANN to predict
the risk level of patients having heart disease. Fig. … On the other hand, Kmeans’ precision and …

… data is performed by using K-means clustering algorithm. … data mining methods like decision
tree, neural network, … was done for the heart disease prediction. The results reveal that SVM …

… In this work, a neural network model using radial basis function with K means clustering has
been implemented using TensorFlow and Keras. The model was run for 10 and 100 epochs …

… Thehybrid clustering model is developed by K-Means … an approach named Vote, which was
a hybrid approach from … proposed a Very Deep Convolutional Neural Network (VDCNN) with …

… [39] Amita Malav, Kalyani Kadam, and Pooja Kamat, “Prediction of heart disease using k-means
and artificial neural network as hybrid approach to improve accuracy,” International …

… Also, other techniques were used to predict cardiac diseases such as Naive … methods for
treating and predicting cardiac disease have recently been established. The hybrid method …

… , Self organizing Maps, k-means etc. are applied for making a group C of representatives to
… Lastly, Neural Network (NN) was applied to prediction process by considering the input data …