Abstract
This paper explores the current manual process of diagnosing and treating malaria patients in developing countries, specifically Nigeria, where healthcare professionals rely on patient interviews and laboratory tests to determine the cause of illness and prescribe treatments. The proposed system aims to automate and streamline this process by utilizing the Structured Systems Analysis and Design Method (SSADM), a widely-used approach for developing modular systems. The system initializes a counter based on patient-reported symptoms, logically processing each symptom to help identify potential conditions. For example, a diagnosis of malaria is suggested when a patient exhibits certain symptoms. The system then generates treatment recommendations and drug prescriptions based on the symptoms identified, saving and printing the results. If the symptoms are insufficient for a diagnosis, the system prompts the patient for further lab tests and consultations with a medical practitioner. This approach seeks to enhance the efficiency and accuracy of the diagnostic process in resource-constrained environments.
Keywords
Artificial Intelligence, Expert System, Malaria Diagnosis, Postrate Cancer Diagnosis, Healthcare
Citations
IRE Journals:
Ikegwuonu Dorathy C., Prof. Ike Mgbeafulike "Revolutionizing Healthcare: The Role of Artificial Intelligence in Medical Support" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 313-322 https://doi.org/10.64388/IREV9I9-1714810
IEEE:
Ikegwuonu Dorathy C., Prof. Ike Mgbeafulike
"Revolutionizing Healthcare: The Role of Artificial Intelligence in Medical Support" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1714810
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