Machine learning in human cancer research


Evidence-based medicine has grown in stature over three decades and is now regarded a key development of modern medicine. The evidence base can be heterogeneous, involving both qualitative knowledge and measured quantitative data. Data analysis in the area of cancer research has for long been the playing field of statisticians but, over the last decade, Machine Learning (ML) methods have also begun to establish themselves an an alternative and promising approach to computer-based data analysis in oncology. In this chapter, we provide a state-of-the-art in the main areas of cancer research in which ML methods are currently being applied, and discuss some of the advantages and disadvantages of their application. We also comment on and illustrate the integration of ML methods in clinical oncology decision support systems

Similar works

Full text



Last time updated on 05/04/2020

This paper was published in RECERCAT.

Having an issue?

Is data on this page outdated, violates copyrights or anything else? Report the problem now and we will take corresponding actions after reviewing your request.