Chapter 1: Predictive analytics and machine learning for medical informatics: A survey of tasks and techniques
Deepti Lamba; William H. Hsu; Majed Alsadhan Department of Computer Science, Kansas State University, Manhattan, KS, United States
Abstract
In this chapter, we survey machine learning and predictive analytics methods for medical informatics. We begin by surveying the current state of practice, key task definitions, and open research problems related to predictive modeling in diagnostic medicine. This follows the traditional supervised, unsupervised, and reinforcement learning taxonomy. Next, we review current research on semisupervised, active, and transfer learning, and on differentiable computing methods such as deep learning. ...
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