Machine Learning Detects Interstitial Lung Disease via Lung Ultrasound
- Researchers have successfully applied machine learning to lung ultrasound images to detect interstitial lung disease in patients diagnosed with idiopathic inflammatory myopathy and systemic sclerosis.
- The findings were published in the journal Arthritis Care & Research on April 30, 2026.
- Fairchild, MD, PhD, who serves as the clinical chief of the division of immunology and rheumatology at Stanford University.
Researchers have successfully applied machine learning to lung ultrasound images to detect interstitial lung disease in patients diagnosed with idiopathic inflammatory myopathy and systemic sclerosis.
The findings were published in the journal Arthritis Care & Research on April 30, 2026.
The study was led by Robert M. Fairchild, MD, PhD, who serves as the clinical chief of the division of immunology and rheumatology at Stanford University.
Beyond its accuracy, [lung ultrasound (LUS)] offers advantages such as low cost, accessibility, no radiation, and sustainability,Robert M. Fairchild, MD, PhD
While lung ultrasound provides these benefits, the research team noted that the technology faces challenges regarding operator dependence and variability in how images are acquired and interpreted.
The integration of machine learning is intended to address these inconsistencies, potentially providing more standardized and accurate detection of interstitial lung disease in patients with these specific connective tissue diseases.