
A new metasurface spectral AI chip enables rapid, accurate diagnosis of meibomian gland dysfunction (MGD) from tissue samples, achieving 96.22% accuracy.
Key Details
- 1Researchers from Peking Union Medical College Hospital and Tsinghua University developed a compact optical AI chip for MGD diagnosis.
- 2The AI chip integrates a spectral convolutional neural network (SCNN) directly onto a CMOS imaging sensor.
- 3Pathological tissue sections from MGD patients and controls were rapidly analyzed, producing spectral feature maps in tens of milliseconds.
- 4The chip identifies MGD with 96.22% accuracy, outperforming conventional RGB image analysis (84%) and matching hyperspectral imaging.
- 5Distinct spectral signatures corresponded with disease severity and biochemical changes in gland tissue.
- 6The device is CMOS-fabricated, enabling potential clinical integration for real-time, objective ocular assessment.
Why It Matters

Source
EurekAlert
Related News

AI Analyzes 66,000 MRI Scans to Map Body Composition Risks
Researchers used AI to analyze over 66,000 whole-body MRI scans, creating a detailed body composition reference map linked to health risks.

Brain-Inspired Training Enhances AI Reliability and Uncertainty Recognition
KAIST researchers developed a brain-inspired AI training method that reduces overconfidence and improves the recognition of unfamiliar data.

AI and PS-OCT Enhance Early Keratoconus Detection
AI combined with polarization-sensitive OCT enables earlier and more accurate detection of subclinical keratoconus compared to standard tomography.