MalariaCare+ is a comprehensive AI-powered diagnostic and clinical decision support system developed to improve the detection, staging, and monitoring of Plasmodium knowlesi, the primary malaria species in Malaysia. The project incorporates sophisticated deep learning techniques, graph-based object detection, and stage-specific classification to precisely identify infected red blood cells, even within densely populated and overlapping blood smear images—an enduring challenge with conventional microscopy. Integrating real-time image analysis, explainable AI visualization, and longitudinal patient monitoring into a mobile-compatible platform, MalariaCare+ empowers clinicians to make quicker, more accurate, and stage-informed treatment decisions. Developed in partnership with the Malaria Research Centre (UNIMAS) and Hospital Kapit, the system is intended for implementation in resource-constrained and endemic environments, advancing Malaysia's malaria elimination efforts while establishing Universiti Malaya as a leader in AI-powered digital health innovation.