A systematic review on machine learning and deep learning techniques in cancer survival prediction

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 pr...

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Bibliographic Details
Published inProgress in biophysics and molecular biology Vol. 174; pp. 62 - 71
Main Authors P, Deepa, C, Gunavathi
Format Journal Article
LanguageEnglish
Published England 01.10.2022
Subjects
Deep Learning
Humans
Machine Learning
Neoplasms
Deep learning
Cancer survival analysis
Machine learning
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Summary: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.
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ISSN:0079-6107
1873-1732
1873-1732
DOI:10.1016/j.pbiomolbio.2022.07.004