Data Science and Healthcare

Data science is often used as an umbrella term to include various techniques for extracting insights and knowledge from complex structured and unstructured data. It often relies on a large amount of data (big data) and the application of different mathematical methods, including computer vision, NLP (or natural language processing), and data mining techniques. Advances in data science have resulted in a wider variety of algorithms, specialized for different applications and industries, such as healthcare, finance, marketing, supply chain, management, and general administration. Specifically, data science methods have shown promise in addressing key healthcare challenges and helping healthcare practitioners and leaders make data-driven decision-making. This chapter focuses on healthcare issues and how data science can help solve these issues. The chapter will survey different approaches to defining data science and why any organization should use data science. This chapter will also present different skills required for an effective healthcare data scientist and discusses healthcare leaders' behaviors that in impacting their organizational processes.

Keywords: Data science, Healthcare, Mathematical models, Machine learning, Natural language processing.