Diagnostic errors can be caused by many reasons such as lack of information necessary for a correct diagnosis, incomplete or erroneous communication between the patient and the healthcare provider, the clinician’s weariness, or even a high level of diagnostic complexity in a short amount of time. Incorrect diagnosis has a negative impact on how a patient is treated. Unnecessary therapies have bad effects on a patient’s condition and they raise medical expenses as well. In the Modified atmosphere of information technology and health care, liver health of patient care can be improved by using the vast opportunity of technology utilization. The conventional methods are still at some lack and substantial unmet requirements are analyzed. Fuzzy logic-based systems could be practiced to reduce these diagnostic errors. Machine learning-based algorithms may be practices to precisely identify a variety of illnesses. Fuzzy systems could be utilized as a supporting tool or as a second opinion to assist doctors make choices on time. This review article provides a comprehensive summary on different fuzzy logic-based systems reported in the existing studies for the findings of liver illnesses.