Dry eye is matched by increased intrasubject variability in tear osmolarity as confirmed by machine learning approach.

In the clinical setting, both mean osmolarity and osmolarity variability in the dry eye group were significantly higher than in the control group. Machine learning techniques showed good classification accuracy. It is concluded that higher variability of tear osmolarity is a dry eye feature.