Abstract

It is vital that tumours are diagnosed and predicted early in cancer research to help the patient clinically. In today’s world, innovative approaches are being developed to minimise or avoid lethal human diseases. Machine Learning is becoming increasingly popular for classifying cancer patients according to their risk of recurrence. Machine learning expands its applications beyond the technical domain, and its pertinence in the medical area is also proliferating. It can also be used in tumour detection because of its ability to evaluate and classify a large amount of complex image data. Machine learning methods may appear to enhance understanding of tumour progression, but a significant amount of evidence must be obtained to use them in everyday clinical practice. The aim of this study is to review, categorise, analyse, and discuss the current developments in human tumour detection using machine learning techniques which help in cancer diagnosis and cure processes.

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