Big Data in Healthcare: Management, Analysis, and Future Prospects: Knowledge Engineering with Big Data Analytics

Machine learning (ML) is a subsection of artificial intelligence that combines or merges statistics and probabilities and finds best solution to facilitate computers to study from prior examples and to detect hard-to-detect patterns in large, noisy, or complex datasets. These characteristics are mainly beneficial in medical applications that need intricate proteomic and genomic measurements. ML techniques like support vector machine, neural networks, K-nearest neighbor, AdaBoost, logistic regression, and random forest are normally applied in cancer identification and discovery. ML has been applied in cancer prognosis and prediction. In this chapter, the top performing algorithms for the analysis of dataset features were discussed. The data used to train the ML models could be huge, and the extraction from these big data is a challenging job.