Multi-Disease Prediction Techniques using Machine and Deep Learning

With the development of technologies, the progress of life, and environmental changes, the number of diseases is increasing day by day. Disease prediction and analysis are important research topics in the medical field. Different techniques and methods are introduced for prediction and analysis. The development of artificial intelligence and its integration into the health sector have produced huge changes in the prediction and analysis of disease. The subset of artificial intelligence known as machine learning and deep learning techniques has contributed different methods and analysis systems for better prediction and classification of diseases. In this article, we present the different machine and deep learning techniques and provide a comprehensive review for the prediction and classification of multi-disease in the healthcare sector. Particularly, this article presents four main contribution summaries for multi-disease prediction, such as statistical, machine, and deep learning techniques for prediction and analysis of multi-disease, different dataset summary presentations for multi-disease prediction and analysis, metrics and evaluation parameters for prediction and classification, and the future direction of research for classification and prediction of multi-disease prediction.