AI for Hantavirus Chest Imaging: Practical Roadmap for Rare Disease

Developing AI for hantavirus pulmonary syndrome chest imaging is challenged by data scarcity, low prevalence, and overlapping findings; future work requires multi-institutional datasets, prevalence-aware evaluation, and multimodal integration with clinical and lab data.

• Data scarcity and low pretest probability in non-endemic areas hinder conventional disease-specific AI development.
• Prevalence-aware evaluation and multimodal integration (imaging + clinical/laboratory/epidemiology) are essential to avoid misleading performance.
• Lessons from COVID-19 AI highlight the need for realistic comparator inclusion, external validation, and careful workflow integration.

Automated summary

RadPigeon summaries are original and for information only. They are not clinical advice.