A systematic review on machine learning and deep learning techniques in cancer survival prediction. (October 2022)

• Record Type: Journal Article
• Authors: P, Deepa; C, Gunavathi
• Is Part Of: Progress in biophysics and molecular biology. Volume 174(2022)
• Page Start: 62
• Page End: 71
• Publication Date: 2022-10
• Subjects: Cancer survival analysis -- Machine learning -- Deep learning; Biophysics -- Periodicals; Biochemistry -- Periodicals; Biophysics -- Periodicals; Molecular Biology -- Periodicals; Biophysique -- Périodiques; Biochimie -- Périodiques; 571.4
• DOI: 10.1016/j.pbiomolbio.2022.07.004
• Languages: English
• ISSNs: 0079-6107

Abstract

Abstract: Cancer is a disease which is characterised by the unusual and uncontrollable growth of body cells. This usually happens asymptomatically and gets spread to other parts of the body. The major problem in treating cancer is that its progress is not monitored once it is diagnosed. The progress or the prognosis can be done through survival analysis. The survival analysis is the branch of statistics that deals in predicting the time of event of occurrence. In the case of cancer prognosis the event is the survival time of the patient from the onset of the disease or it can be the recurrence of the disease after undergoing a treatment. This study aims to bring out the machine learning and deep learning models involved in providing the prognosis to the cancer patients.