Soft Computing and Data Mining Techniques for Dengue Detection: A Review

Dengue fever is a viral illness that is transmitted to humans by the bite of an infected mosquito. It is most common in tropical and subtropical countries, where it affects a significant number of people. The condition must be treated medically, and if it is not treated appropriately or if there is a delay in the therapy, it might result in the patient's death. Therefore, there is a need for an early diagnosis of the condition so that therapy is being provided as and when necessary. In this review article, our goal is to investigate and discuss the soft computing approaches that, when combined with bioinformatics, may be useful in the future for the early diagnosis of dengue fever. The major purpose of this review article is to investigate and evaluate the various soft computing approaches and bio-models that have been used on the Dengue datasets in previous research. This article provides an overview of numerous different methods that may be utilized in the diagnosis of dengue fever. The review study might be of assistance in both encouraging the researchers and recommending more substantial effort with regards to the aforementioned future tasks and difficulties.