Study on Health Issue Identification Using Deep Learning and Convolutional Neural Networks

Changing lifestyles made humans close to health issues. Healthcare systems have also improved a lot in identifying health-related issues. However, accurate analysis and correct identification of the disease have not been performed so far. This is due to the lack of accurate analysis of small medical images. Deep learning helps in that, with the help of deep neural networks, proper decisions can be made in the healthcare system. This article tried to analyze different healthcare issue identification done with the DNN model. Based on these analyses, the work deep learning model becomes the stair for identifying health issues. Deep learning has the potential to be one of the most significant breakthroughs in medical diagnosis. It is a subfield of artificial intelligence that enables machines to use learned algorithms to make decisions. This article highlights the applications, challenges, and future developments of deep learning in disease diagnosis. Deep learning and convolution neural networks (CNNs) are changing the world of medical diagnosis. With their ability to analyze high-dimensional data, these technologies have revolutionized the healthcare industry, improved patient outcomes, and reduced medical errors. In this document, we explore the many benefits and challenges of applying deep learning and CNNs in medical diagnostics.