Sugiura Hiroki

Hashimoto Yohei, Kiwaki Taichi, Sugiura Hiroki, Asano Shotaro, Murata Hiroshi, Fujino Yuri et al.

Deep learning predicting 10-2 visual fields from OCT improved significantly when corrected with 24-2/30-2 visual fields, potentially reducing the need for additional 10-2 tests.

Hashimoto Yohei, Asaoka Ryo, Kiwaki Taichi, Sugiura Hiroki, Asano Shotaro, Murata Hiroshi et al.

A deep learning model accurately predicted central 10° visual fields from SD-OCT scans in glaucoma, offering a potential objective tool for assessing functional loss.

Yousefi Siamak, Kiwaki Taichi, Zheng Yuhui, Sugiura Hiroki, Asaoka Ryo, Murata Hiroshi et al.

This study found a machine learning index detects glaucoma progression in visual fields earlier than current methods, potentially allowing for faster clinical intervention and improved patient outcomes.