MaternalU5Triage: An AI-Powered Clinical Decision Support System for Maternal, Neonatal and Under-Five Emergency Triage

MaternalU5Triage: An AI-Powered Clinical Decision Support System for Maternal, Neonatal and Under-Five Emergency Triage This publication presents the MaternalU5Triage research proposal, a comprehensive technical and implementation framework for the development of an artificial intelligence (AI)-powered clinical decision support system designed to support maternal, neonatal, and under-five emergency triage in primary healthcare and other resource-constrained settings. The proposal integrates evidence-based clinical guidelines, explainable artificial intelligence (XAI), machine learning, interoperability standards, and responsible AI governance to support timely clinical assessment while maintaining human clinical oversight. The system is intended to complement—not replace—the judgment of qualified healthcare professionals. The document includes: Background and rationale for AI-assisted maternal and child health triage. System architecture and technical design. AI methodology and explainability considerations. Clinical decision support workflow. Data governance, privacy, cybersecurity, and ethical considerations. Interoperability using standards such as HL7 FHIR, SNOMED CT, ICD-11, and LOINC. Validation, monitoring and evaluation, implementation, and sustainability frameworks. An extensive bibliography covering AI, digital health, maternal and child health, clinical decision support, interoperability, implementation science, and responsible AI. This work is intended as a research and development proposal to support scientific collaboration, funding applications, and future implementation research. Disclaimer: This document describes a research and development project and does not represent a clinically approved medical device or deployable clinical system. Any future implementation should be preceded by appropriate regulatory review, clinical validation, ethics approval where applicable, and implementation in accordance with relevant national regulations, institutional governance, and applicable international standards.