Pilot study demonstrates machine learning classifies tear film lipid layer patterns in eye care, suggesting its use for monitoring.
The proposed ML model can classify TFLL patterns from self-acquired SBI images with good accuracy and replicate typical TFLL spreading dynamics. These findings support its potential application to dynamic monitoring in personalized eye care and home-based dry eye management.
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Okazaki et al. (2026) studied this question.
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