Abstract Machine learning is a powerful tool that can be used to solve a wide range of
problems in various applications and industries. The healthcare sector has faced specific …

In this chapter, we provide a brief overview of applying machine learning techniques for
clinical prediction tasks. We begin with a quick introduction to the concepts of machine …

The exponential proliferation of heterogeneous health-related information presents
unprecedented opportunities for improving patient care. Health-related data arise from …

• Multidisciplinary partnership between technical experts and end-users, including clinicians,
administrators, and patients and their families, is essential to developing and implementing …

Significant progress in science related to an understanding of disease and treatment has
contributed to an increase in the life span of people. With increasing urbanization and …

Traditional research techniques do not work well in the dynamic environment of big data in
the healthcare industry, which is characterized by enormous numbers, complexity, and …

The world is currently undergoing a rapid transformation in technology that will drastically
change our lives, and potentially redefine what it means to be human. Machine learning has …

Background Predictive modeling is fundamental to transforming large clinical data sets, or
“big clinical data,” into actionable knowledge for various healthcare applications. Machine …

Machine learning (ML) models have proven their potential in acquiring and analyzing large
amounts of data to help solve real-world, complex problems. Their use in healthcare is …

In the emerging era of big data, larger available clinical datasets and computational
advances have sparked a massive interest in machine learning-based approaches. The …