A comprehensive review of deep learning in lung cancer
This is a review paper, so it is incremental and aims to inform researchers and clinicians about deep learning applications in lung cancer diagnosis.
The paper reviews the historical development and fundamentals of cancer diagnosis, highlighting the ineffectiveness of current methods and the need for more intelligent approaches, but does not report specific results or numbers.
To provide the reader with a historical perspective on cancer classification approaches, we first discuss the fundamentals of the area of cancer diagnosis in this article, including the processes of cancer diagnosis and the standard classification methods employed by clinicians. Current methods for cancer diagnosis are deemed ineffective, calling for new and more intelligent approaches.