Advances in Big Data and Machine Learning in Cancer Detection in Women-Associated Cancers

Abstract

Machine learning (ML) is a type of artificial intelligence (AI) that employs a range of statistical, deterministic and optimization methods to automatically learn and improve performance from fresh data and prior experiences without the need for explicitly coded instructions. When working with complex, massive, high-dimensional data, machine learning algorithms are usually capable of identifying crucial features and probable rules that are difficult to find using standard statistics. Nowadays, cancer diagnosis is acquiring exponentially more data from the past and projecting therapy strategies based on data analysis. Regrettably, previous approaches of applying machine learning algorithms were unable to meet the new problems of large data, particularly scalability. New big data technologies have recently evolved, lowering the cost of keeping vast amounts of data from breast cancer patients and enabling real-time information analysis by combining all stored and flowing data. This chapter attempts to showcase new breakthroughs in big data and machine learning techniques that are being used in the early detection of cancers that are largely linked with women all over the world.