Fuzzy Systems in Medicine and Healthcare
Deepak K. Sharma, Sakshi, Kartik Singhal · 2020
Healthcare and medicine are one of the most innovative fields that are employing soft computing-based techniques with the aim to support human decision making and improve expertise in a field of acute fuzziness. In order to deal with the uncertainty and vagueness of diseases and health, fuzzy logic-based systems have become one of the most prominent tools for the industry. Fuzzy systems provide crucial decision-making capabilities as they employ more approximate reasoning rather than dealing in a binary fashion. The fuzzy logic system is a knowledge rule-based system. It manoeuvres uncertainty in data by creating propositions based on expert knowledge and mapping relative consequences. Based on the concept of many-valued logic, fuzzy logic systems deal in more humanlike cognitive semantics. With the advent of improving technical know-how, newer methods amalgamating fuzzy logic with other AI techniques have further broadened the scope of fuzzy systems and driven a paradigm shift in the healthcare industry by advancing various applications from diagnosis methods for anaemia or monitoring the patient&s;s condition during a heart surgery to optimising medical databases and information retrieval processes. This chapter explores the role of fuzzy logic in medicine and healthcare and aims to provide a study of the already existing methodology followed in the industry and the scope of newer hybrid techniques. This chapter demonstrates the application of fuzzy logic to provide a platform for encapsulating the subjective decision-making process in an algorithm suitable for computer implementation.