An Overview of Machine Learning and Its Challenges in Applying to Healthcare

Abstract

The healthcare sector is globally facing a call for transformation due to its growing complexity and its increasing shortage of professionals. Given the potentials of Artificial Intelligence, especially its Machine Learning branch, to drive this transformation, this chapter provides an overview of the Machine Learning field. We describe the building blocks of a typical Machine Learning system, and provide an overview of different types of Machine Learning algorithms and their applications. For each type, we discuss several basic algorithms, highlighting their shortcomings. Informing about these shortcomings is important because addressing them has led to the development of many advanced Machine Learning algorithms. We discuss the ways that a number of such (advanced) algorithms have been applied to the healthcare domain. It is important to address the challenges associated with the application of Machine Learning into practice, such as the issues related to privacy, security and ethics. Therefore, we also review a number of such challenges that should be addressed for ensuring a trustworthy and responsible application of Machine Learning to healthcare.

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