  Single-cell RNA sequencing (scRNA-seq) provides a high throughput,
quantitative and unbiased framework for scientists in many research fields to
identify and characterize cell types within heterogeneous cell populations from
various tissues. However, scRNA-seq based identification of discrete cell-types
is still labor intensive and depends on prior molecular knowledge. Artificial
intelligence has provided faster, more accurate, and user-friendly approaches
for cell-type identification. In this review, we discuss recent advances in
cell-type identification methods using artificial intelligence techniques based
on single-cell and single-nucleus RNA sequencing data in vision science.
