Abstract
Heart failure and other chronic diseases have posed huge challenges to the healthcare sectors across different country. As a result of inadequate tools and techniques to address the challenges, numerous patients have died while several others have experienced a decreased quality of life with various degrees of psychological burdens. With the revivification of artificial intelligence in the 1990s, computational intelligence (CI) tools have since been adopted in developing clinical decision support systems for heart disease diagnosis to ensure qualitative healthcare services. In this chapter, we describe some notable CI techniques and their clinical applications as it relate to heart failure risk prediction. Furthermore, the strength and limitation of these CI techniques in terms of accuracy and computational complexity are also discussed. Lastly, the potential role of CI in healthcare delivery systems is equally described.
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