Abstract
Dengue fever is caused due to the mosquito (Aedel aegypti) bite. The symptoms of this fever are similar to other fevers such as Malaria, Chikungunya and Zika. A common sign of Dengue fever is the sharp fall of blood platelet count, amongst other a host of other confusing symptoms, which makes Dengue difficult to diagnose, especially by an inexperienced physician. The purpose of this study is to outline a decision support system (DSS) which would come to the aid of detection of Dengue fever by carrying out an analysis of AHP and fuzzy AHP (FAHP) methodology. The data of confirmed Dengue as diagnosed by a physician is picked up, examined independently using AHP and FAHP approach, the results obtained are then compared with the diagnosis report of an expert doctor. The outcome is encouraging and indicates that expert systems can be leveraged for the diagnosis of Dengue and can be a useful tool for non-expert physicians
Highlights
The most important thing in the medical field is proper and accurate diagnosis as it is challenging even for a well-qualified doctor having ample experience in handling thousands of comparable cases
The hierarchal structure of Analytic Hierarchy Process (AHP) methodology makes it fit for synthesizing a variety of factors of a complex decision- making process in a hierarchic manner, making it simple to combine the parts in a whole and has the potential to model the unstructured information associated with data like a human centric approach
As per the decision maker’s pairwise comparisons of the measure, AHP generates a weight for each measure and it signifies dominance of the measure which has a high value of the weight
Summary
The most important thing in the medical field is proper and accurate diagnosis as it is challenging even for a well-qualified doctor having ample experience in handling thousands of comparable cases. The existing symptom of an infectious disease is an indicator for other problems as well. To lessen this possibility, the concerned specialist sticks to a particular decision sequence for a given illness trajectory of the patient. It increases the risk of loss of life due to unidentified illness and non-correctable errors in a timely manner
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