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Design and implementation of medical diagnosis system - case study of malaria

 Department: Computer Science  
 By: usericon olagok01  

 Project ID: 8844
   Rating:  (5.0) votes: 1
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   Price:₦4000
Abstract
Malaria remains a severe public health challenge, particularly in tropical and subtropical regions, causing significant morbidity and mortality due to challenges in timely and accurate diagnosis. Traditional diagnostic methods, such as microscopy and Rapid Diagnostic Tests (RDTs), are often hindered by the need for specialized equipment, trained personnel, and laboratory infrastructure, which are scarce in resource-poor and rural settings. This project addresses this critical gap by designing and implementing an intelligent, web-based medical diagnosis system for malaria. The system utilizes a hybrid approach, integrating a rule-based expert system with machine learning algorithms, including Decision Trees, Random Forests, and Naive Bayes, to analyze patient-reported symptoms such as fever, chills, vomiting, and headache. Developed using Python and accessible via a user-friendly web interface, the system provides a preliminary diagnosis, serving as a decision-support tool to aid healthcare workers and individuals in areas with limited medical resources. By enhancing the speed, accessibility, and accuracy of initial malaria screening, this system aims to reduce misdiagnosis, enable earlier treatment, and ultimately contribute to improved health outcomes in affected communities....
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