Abstract
Clinical decision support systems (clinical DSSs) are widely used today for various clinical applications such as diagnosis, treatment, and recovery. Clinical DSS aims to enhance the end‐to‐end therapy management for the doctors, and also helps to provide improved experience for patients during each phase of the therapy. The goal of this chapter is to provide an insight into the clinical DSS associated with the highly prevalent heart rhythm disorder, atrial fibrillation (AF). The use of clinical DSS in AF management is ubiquitous, starting from detection of AF through sophisticated electrophysiology treatment procedures, all the way to monitoring the patient's health during follow‐ups. Most of the software associated with AF DSS are developed based on signal processing, image processing, and artificial intelligence techniques. The chapter begins with a brief description of DSS in general and then introduces DSS that are used for various clinical applications. The chapter continues with a background on AF and some relevant mechanisms. Finally, a couple of clinical DSS used today in regard with AF are discussed, along with some proposed methods for potential implementation of clinical DSS for detection of AF, prediction of an AF treatment outcome, and localization of AF targets during a treatment procedure.