This paper evaluates the role of artificial intelligence (AI) in interstitial lung disease (ILD) — covering pattern recognition on imaging, diagnosis support, and disease surveillance/monitoring over time.
AI tools demonstrate promise in automating CT pattern recognition and providing decision guidance for ILD diagnosis and progression tracking, though specific accuracy metrics or outcome numbers are not extractable from the provided abstract alone.
No full-text data provided; specific performance metrics, study populations, and comparators cannot be confirmed from the available metadata alone.
AI-assisted CT analysis may support clinicians in earlier and more consistent ILD diagnosis and longitudinal surveillance. Clinicians should remain aware that AI tools in ILD are evolving and require validation in diverse, real-world populations before broad adoption.
