Quantum Machine Learning can be considered one of the transformational technologies in precision medicine and drug discovery because quantum computing combines immense processing power with high capability, predictive machine learning. This chapter will discuss the potential for QML to revolutionize complex biological data analysis to rapidly identify disease biomarkers and highly personalized treatment approaches. The chapter describes the two superior performances that can be achieved by quantum algorithms in simulating molecular interactions, and thereby drastically reducing time and cost in drug development. It also discusses key applications that include quantum-enhanced neural networks and support vector machines to diagnose diseases and predict outcomes of treatments. Challenges regarding scalability, noise reduction, and hardware limitations are discussed together with some very promising future directions. When quantum technology has reached full maturity, the opportunities it will give to machine learning will provide unparalleled breakthroughs in medical research.