Deep Learning for Cancer Diagnosis, Utku Kose,Jafar Alzubi, Editör, Springer, London/Berlin , Singapore, ss.249-267, 2021
Cancer is among serious health problems with an uncertain and complex
structure that causes fatal results. Cancer is a disease that consists of uncontrolled
proliferation of cells in different organs, whose clinical appearance, treatment and
approach are different from each other and that should be controlled in the early
stages. The cancer burden should be estimated in order to determine priorities for
cancer control. In this context, there are many studies on diagnosis and treatment
methods and a rapid development is observed in this regard. The aim is to increase
the survival rate of people with cancer. In order to achieve this goal effectively,
early and accurate diagnosis is especially important in the treatment of cancer, as
it causes fatal results. It is known that cancer is very difficult to diagnose in the
early stages and accurately with traditional diagnostic methods. At this point, the
artificial intelligence, a new or current approach, comes to the agenda. Developments
in this area offer very important opportunities in cancer diagnosis as in many areas.
Therefore, in this study, deep learning approaches which are an artificial intelligence
technique in the literature for the diagnosis of cancer disease are examined, and the
applications in the literature on how these approaches are used are included. Since
the subject of the study is up to date, it is considered that the study will be a guide
for people or institutions working in this field.