AI presents a significant opportunity to enhance the use of Chest X-rays (CXRs), particularly for active case finding for tuberculosis. While adoption is growing, especially in developing nations, it's still in its early stages and heavily dependent on donor funding.
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This proposed AI CXR Index aims to guide stakeholders in prioritising and promoting adoption tailored to each country's needs. Analysis reveals key drivers, including the extent of need, intent, and ability to roll out AI. Recommendations are provided for stakeholders to facilitate adoption and effectiveness.
Through comprehensive analysis, four key dimensions driving the use of AI for CXRs have been identified: the extent of need, level of awareness, intent, and interest, and the ability to roll out AI technology. These dimensions encompass various factors, such as the shortage of radiologists, awareness among decision-makers, infrastructure availability, and regulatory frameworks.
Countries were further categorised into five archetypes based on their scores, ranging from Frontrunners ready for scale to Skeptics with the ability but lacking intent. This classification facilitates tailored support from stakeholders to each group of countries.
Lastly, several recommendations have been articulated for key stakeholders, including AI and hardware companies, donors, multilaterals, and high TB-burden countries, aimed at fostering greater adoption and effectiveness of AI for CXRs.
