Oğuz, AbdulhalıkErtuğrul, Ömer Faruk2024-12-242024-12-242023978-032396129-5978-032399681-5https://doi.org10.1016/B978-0-323-96129-5.00003-2https://hdl.handle.net/20.500.12604/4097The golden era of machine learning has been ushered in by deep learning (DL), which is the most vital representative of artificial intelligence. DL, in contrast to its forerunners, is exceptional at working with large datasets, merging various prominent techniques, and assuring the nearly flawless execution of numerous tasks across many areas. Since DL has been so successful, it is now essential for resolving medical issues. DL and derivative methodologies are important because early diagnosis is essential for human survival. In this study, the bibliometric summary of the topic of interest is examined, and the size of the huge data set resources employed in DL is described. The most current and productive investigations are then highlighted, followed by an in-depth study of DL techniques. Finally, by examining DL models applied to medical applications, the potential for early detection is investigated. This work, in our opinion, will help define DL for less seasoned academics and provide guidance on how DL might be used to the early identification and treatment of medical issues. © 2023 Elsevier Inc. All rights reserved.eninfo:eu-repo/semantics/closedAccessartificial intelligenceDeep learningmedical diagnosismedicineneural networkBook Chapter140N/A2-s2.0-8516109581310.1016/B978-0-323-96129-5.00003-2