Machine learning in human cancer research
Abstract
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- info:eu-repo/semantics/publishedVersion
- info:eu-repo/semantics/bookPart
- 脌rees tem脿tiques de la UPC::Inform脿tica::Intel路lig猫ncia artificial::Aprenentatge autom脿tic
- Cancer -- Research
- Cancer research
- Machine learning
- Data analysis
- Decision support systems
- C脿ncer -- Investigaci贸
- Aprenentatge autom脿tic
- Sistemes d'ajuda a la decisi贸