Published Paper Details:

Having access to quality health care is crucial to surviving in life. However, getting an appointment with a doctor when you're sick can be difficult. The health care sector is expanding and has a profound impact on many facets of human existence. The healthcare sector is developing in tandem with technological innovation. Rapid technological advancements in the medical sciences promise improved methods of disease prevention, diagnosis, and treatment. Artificial intelligence (AI) is undergoing a sea change due to its numerous applications; for instance, it is reshaping the healthcare industry by allowing for better monitoring of patients with chronic diseases. Researchers have their work cut out for them as they try to streamline the architecture and management of intelligent delivery systems as a whole. The vast majority of these systems are driven by cutting-edge learning algorithms like Convolution Neural Network. The Convolutional Neural Network (CNN) algorithm is frequently used as an illustrative example of DL architecture. With the arrival of CNN hardware accelerators and a subsequent increase in the quantity of available annotated data, the field of CNN research and development has experienced a recent uptick, resulting in benchmarks being implemented on a wide range of different applications. For this meta-analysis, researchers looked for publications published between January 1, 2012 and June 6, 2022 in the databases Ovid-MEDLINE, Embase, Science Citation Index, and Conference Proceedings Citation Index. It was considered valid study to compare the diagnostic precision of deep learning models to that of healthcare professionals utilising medical imaging.