In recent years, the successful implementation of human genome project has made people
realize that genetic, environmental and lifestyle factors should be combined together to study cancer due
to the complexity and various forms of the disease. The increasing availability and growth rate of ‘big
data’ derived from various omics, opens a new window for study and therapy of cancer. In this paper,
we will introduce the application of machine learning methods in handling cancer big data including the
use of artificial neural networks, support vector machines, ensemble learning and naïve Bayes classifiers.
Cultivating historical heritage area vitality using urban morphology approach based on big data and machine learning
