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Updated: May 20, 2026

A Point-of-Care Method with Integrated Decision Support Tool to Estimate Anemia at Population Level
Published on: January 19, 2024
Designing AI tools to advance health equity in resource-constrained low- and middle-income countries
Anindya Pradipta Susanto1,2,3, David Lyell1, Bambang Widyantoro4
1Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW, Australia.
Abstract:
In the resource-constrained settings, shortages of health workers and underdeveloped infrastructure hinder the delivery of equitable, high quality care. This perspective outlines strategic principles to support the design of AI tools that are genuinely beneficial in low-resource contexts: adopting problem-driven approaches, understanding the socio-technical context, selecting appropriate clinical tasks, and ensuring point-of-care accessibility, clinical comprehensibility, and actionable recommendations, ultimately improving clinicians' decision-making and promoting health equity in low- and middle-income countries.
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