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Applied Machine Learning to survival prediction of elderly cancer patients: Systematic Review
Machine Learning (ML) is being successfully used in many science areas, medicine being no exception. On the other hand, cancer is a heterogeneous disease consisting of various sub- types and possible treatments that generate a lot of data (Big Data). This study sets out to identify, evaluate and interpret published research that examines how predicting the outcome of treating cancer can benefit from making use of ML. To achieve this, a systematic review of the literature was conducted. This review resulted in finding 1,855 studies, 32 of which were identified as primary studies. They were then classified according to research area and the aspect of ML they focus on. The results show gaps in current research as no studies were identified on ML using Comprehensive Geriatric Assessment (CGA), a fundamental tool that is used to improve caring for elderly patients with cancer.