Many regions continue to face severe challenges in providing prompt and correct diagnosis of diseases like typhoid, malaria, and associated ailments, especially in underprivileged populations with inadequate medical infrastructure. Conventional diagnostic techniques that depend on laboratory testing and professional advice are frequently unavailable, which causes delays in the start of therapy and unfavorable health consequences. This study suggests creating a knowledge-based patient self-assessment and diagnostic system for typhoid, malaria, and related illnesses as a solution to these problems. The system intends to enable people to evaluate their symptoms, obtain preliminary diagnoses, and obtain prompt recommendations for additional action without the need for direct medical assistance by utilizing database approaches and medical knowledge representation. Key issues addressed include improving healthcare accessibility, ensuring diagnostic accuracy based on patient-reported symptoms and medical guidelines, enhancing user-friendliness and acceptance, implementing robust data security and privacy measures, and integrating seamlessly with existing healthcare infrastructure. Through the development of this knowledge-based system, this study seeks to revolutionize healthcare delivery by providing accessible, accurate, and patient-centric diagnostic solutions for malaria, typhoid, and related diseases. Lastly, knowledge discovery database (KDD) technique is implemented using the Hypertext Pre-Processor (PHP) programming language to build the user application interface for the users of the diagnostic system. By addressing the unique challenges faced by underserved communities, the system has the potential to significantly improve health outcomes and reduce the burden of infectious diseases in these regions.

Malaria Typhoid Fever Knowledge Discovery Database Techniques Patient Self-assessment Diagnostic System Health Technology Disease Diagnosis Expert Systems Clinical Decision Support.