Challenges and Prospects of Implementing C NNs in Healthcare Diagnostics

Healthcare is closely related to human life, and it is one of the most important research fields in contemporary science. Healthcare is everywhere in human life. There is no doubt that when people have a disease, timely treatment is required. This article discusses a kind of Artificial intelligence which is the deep learning called Convolutional neural networks in healthcare. Doctors use Convolutional Neural Networks (CNNs) in disease prediction and detection like some kinds of common disease and cancer. CNNs reached a pretty great performance in healthcare. It has high efficiency and accuracy. This article shows common diseases such as pneumonia, heart disease and diabetes also this article demonstrates cancer such as lung cancer, skin cancer and prostate cancer. As results, those different disease prediction applications have shown CNN is a powerful and useful tool for healthcare. However Artificial intelligence still has lots of big challenges which include explanation, interactivity, adaption, privacy and so on. In the future, AI in healthcare is still bright even if there are so many difficulties. With continuous investigations, the explanation of algorithms is going to become clear, transfer ability would be better so that could save a lot of money and labors. It is expected to bring to more robust, safe, and widely applicable medical diagnostic tools.