Olaide Nathaniel Oyelade, N Owamoyo


Clinical diagnosis is gradually shifting into the homes of patients. This swing is owned to humanizing efforts geared towards the creation of more approximate medical diagnostic reasoning algorithm (MDRA). Researchers have crafted different models to make autonomous approach, clinicians have built their study and experienced on how to tackling diagnostic tasks.  Some of these models are based on statically, mathematical, fuzzy and rule based. Despite their different approaches, they are all oriented towards a MDRA with higher precision. This paper chronicles a list of medical diagnostic algorithms, and then x-rays their key features. Furthermore, a careful study is carried out to identify their various weaknesses as well highlights their benefits over the others. Meanwhile, a comparative study of the MDRAs is presented in this paper. This comparison is metricized around the reasoning mechanism in the algorithm, the accuracy or approximation of diagnosis and the type of ailment they are best used to diagnose. This will help enlighten and chart the course for those who might intent to build a more approximate and efficient MDRA from a hybrid of existing ones. This paper concludes with a discussion into the future research, which are yet to be made in MDRA development

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