<![CDATA[Addressing morbidity and mortality rates among children under five years old in developing nations is a pressing public health priority. The global standard, Integrated Management of Childhood Illness (IMCI) , often faces significant hurdles in implementation, namely the scarcity of trained staff and a heavy dependence on outdated, manual, chart-based diagnostics. This reliance leads to a higher risk of clinical errors and dangerous treatment delays. To overcome this, our research focused on designing, implementing, and validating a novel web-based expert system that fully digitizes the IMCI clinical decision-making process for children aged 2 months to 5 years. Built on a modern full-stack architecture (SvelteKit, Node.js, MySQL) , the core diagnostic logic employs the Forward Chaining inference method , allowing the system to systematically process symptoms and arrive at a precise diagnosis. Rigorous functional testing (Black Box) showed a 100% compliance rate , while structural analysis (White Box) confirmed the implementation of a strict exact match rule mechanism. Crucially, the system demonstrated a high clinical accuracy rate of 90.7%. This resulting application serves as an efficient digital instrument for democratizing IMCI clinical knowledge, promising a significant boost in the speed and consistency of primary healthcare services, especially in underserved regions.]]>
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