A framework for cell phone based diagnosis and management of priority tropical diseases

摘要

Malaria, pneumonia, tuberculosis, typhoid fever, amebiasis, and diarrheal diseases are considered existing global health priorities. This is because of their global prevalence, especially in most developing (tropical) countries. These conditions pose a lot of challenges to global health and wellbeing due to their increasing morbidity and mortality rates; a challenge that has been attributed to poor medical infrastructure, poor diagnosis and management of these diseases. These conditions are known to present with similar symptoms at different stages of their pathogenesis and thus can become “confusable” with each other. Medical practitioners attempting to diagnose and manage these conditions are therefore expected to manage large amounts of information (which can sometimes become unwieldy and time wasting) in order to arrive at an accurate and timely diagnosis. Medical facilities can be freed up through the adoption of mobile devices for early diagnosis of some of the tropical conditions. In this paper, we present a framework for a cell phone based intelligent system (based on fuzzy logic and AHP engines) for the diagnosis of some tropical global health priorities. Fuzzy logic and the analytic hierarchy process (AHP) are known to resolve the conflicts arising from ambiguity, uncertainty, and imprecision of information, and thus can be harnessed in the analysis of information supplied by patients in the cell phone-based diagnosis of confusing tropical diseases.