| dc.description.abstract | Globally, cataracts are among the major causes of
blindness. Previously, ophthalmologists used objective lens
examination and visual acuity tests, to diagnose cataracts. In
general, this method of manual diagnosis has drawbacks in
terms of accuracy, inter and intra observer consistency and
most importantly, consistency across cases. The current
studies incorporate AI and ML to evaluate the digital eye
images for the cataract classification and staging with greater
objectivity. This paper examines 18 prior studies on how the
use of AI in diagnosing cataracts outperforms physicians even
without the assistance of the former, which could contribute
to the improvement of decision-making services and global patients' accessibility to quality eye care. The prominent
obstacles to the establishment of the technology include data
privacy, monitoring, and acceptability among the physicians.
However, AI has a great potential to help improve precision
medicine and individualized treatment of patients with
cataracts. | en_US |
