Abstract: Machine learning as well as Deep learning applications had qualified huge growth in different medical fields such as medical image analysis as well as other related data due to the fact of the convenience of several data sets to train the learning algorithms in multimodal modes. However, machine learning and deep learning can distinguish patterns in healthcare data to enhance diagnosis and prognosis. The most utilized machine learning and deep learning techniques for healthcare applications are autoencoder, restricted Boltzmann machine, deep belief network, recurrent neural network, convolutional neural network, generative adversarial network, neural networks, and support vector machine. This paper aimed to illustrate the different applications associated with these learning algorithms that focus on healthcare field. It also illustrates the high-tech methods utilized to employ the learning algorithms.