Eye health and vision have widespread and profound implications for many aspects of life,
health, sustainable development, and the economy. Yet nowadays, many people, families …

Artificial intelligence (AI) has lately witnessed an age of tremendous expansion across
several industries, including healthcare. In recent years, substantial advancements in AI …

With the advancement of computational power, refinement of learning algorithms and
architectures, and availability of big data, artificial intelligence (AI) technology, particularly …

Deep learning (DL) has been successfully applied to the diagnosis of ophthalmic diseases.
However, rare diseases are commonly neglected due to insufficient data. Here, we …

Background The ophthalmology field was among the first to adopt artificial intelligence (AI)
in medicine. The availability of digitized ocular images and substantial data have made …

Real-time intraoperative guidance is essential during various surgical treatment of many
diseases. Aggregation-induced emission (AIE) materials have shown great potential for …

Electrophysiological methods, that is M/EEG, provide unique views into brain health. Yet,
when building predictive models from brain data, it is often unclear how electrophysiology …

Purpose: Recently, laser refractive surgery options, including laser epithelial keratomileusis,
laser in situ keratomileusis, and small incision lenticule extraction, successfully improved …

Purpose: Selecting the optimal lens size by predicting the postoperative vault can reduce
complications after implantation of an implantable collamer lens with a central-hole (ICL with …

Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the
diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic …