AI retinal age estimation and ocular health research

Medical research has advanced in using ocular data to assess systemic health and treat vision loss. Researchers have developed artificial intelligence models capable of estimating a person’s biological age by analyzing retinal photographs.

Initial studies involving over 70,000 individuals demonstrated that these AI models can estimate age with an average deviation of less than three years. A significant discrepancy between biological and chronological age serves as an indicator for increased risks of cardiovascular disease, respiratory issues, cancer, and dementia. Research noted that these correlations vary by gender; for instance, retinal age in men is more strongly linked to metabolic syndrome markers, while in women, it is more closely associated with vascular factors.

In addition to diagnostic advancements, clinical developments have emerged regarding vision restoration. Researchers have successfully used hydroxypropyl methylcellulose (HPMC), an inexpensive surgical gel, to treat ocular hypotony. In small clinical series, the gel has been used to restore intraocular pressure and eye geometry, helping to stabilize the retina and lens in patients with collapsed eye structures.