Detecting cervical cancer using deep learning methods

Cervical cancer is the fourth most common type of cancer in women. It is the second most common type of cancer in developed countries. It is a type of cancer that develops in the cervix, known as the "cervix." Cells known as precursors of cancer can occur when the layer of cells that form the surface of the cervix transforms into abnormal cells. Affecting more than 500,000 women each year, cervical cancer is one of the most common types of cancer in women. Cervical cancer can spread to deeper tissues and other organs depending on its stage. It is a type of cancer that can be prevented when diagnosed early. Mutations in the DNA of healthy cells in this area result in cervical cancer. Healthy cells divide throughout a specific cycle, continue their lives, and when the time comes, they give way to young cells. As a result of mutations, this cell cycle is disrupted, and cells multiply uncontrollably. Abnormal cell growth causes the formation of masses or structures called tumors. This negative growth is called cancer if malignant, such as invading other surrounding and distant body structures. Early detection of these cancer cells is crucial for treatment. In this thesis study, an artificial intelligence-based hybrid model that can detect cervical cancer early has been developed. Thanks to this developed artificial intelligence-based system, cervical cancer can be detected earlier. In addition, the model we developed can be used for preliminary diagnosis in places with no experts and to relieve experts' workload. The model developed in the thesis study was compared with pre-trained models accepted in the literature. The developed model achieved better results than these models.