Chiang Michael

Bolo Kyle, Apolo Aroca Galo, Pardeshi Anmol A, Chiang Michael, Burkemper Bruce, Xie Xiaobin et al.

Deep learning algorithms on ANTERION AS-OCT accurately detect the scleral spur, outperforming human graders. This enhances angle closure assessment and IOL calculations, improving clinical utility.

Randhawa Jasmeen, Chiang Michael, Porporato Natalia, Pardeshi Anmol A, Dredge Justin, Apolo Aroca Galo et al.

An OCT deep learning classifier consistently detected angle closure across diverse populations, showing strong agreement with human examiners. This tool could aid ophthalmologists in assessing angle status.

Shen Alice, Chiang Michael, Pardeshi Anmol A, McKean-Cowdin Roberta, Varma Rohit, Xu Benjamin Y

This study found deep learning misclassifications for angle closure from AS-OCT are explained by disagreement between anterior segment and angle parameters, potentially improving classifier performance and clarifying angle closure definitions.

Chiang Michael, Guth Daniel, Pardeshi Anmol A, Randhawa Jasmeen, Shen Alice, Shan Meghan et al.

A CNN accurately detected angle closure in goniophotographs, performing comparably to an expert and better than most human graders. This offers an automated tool for remote glaucoma risk screening.

Xu Benjamin Y, Chiang Michael, Chaudhary Shreyasi, Kulkarni Shraddha, Pardeshi Anmol A, Varma Rohit

Deep learning accurately detects angle closure and PACD from AS-OCT images, offering a promising automated tool to improve angle assessment and eye care access, especially in high-risk groups.