Kiwaki Taichi

Detection of Longitudinal Visual Field Progression in Glaucoma Using Machine Learning.

Machine learning analysis detects progressing eyes earlier than other methods consistently, with or without confirmation visits. In particular, machine learning detects more slowly progressing eyes than other methods.

Predicting the Glaucomatous Central 10-Degree Visual Field From Optical Coherence Tomography Using Deep Learning and Tensor Regression.

The Humphrey 10-2 VF can be predicted from OCT-measured retinal layer thicknesses using deep learning and tensor regression.

Predicting 10-2 Visual Field From Optical Coherence Tomography in Glaucoma Using Deep Learning Corrected With 24-2/30-2 Visual Field.

The performance of a DL model to predict 10-2 VF from macular OCT was improved by the correction with HFA 24-2/30-2.

Improving Visual Field Trend Analysis with OCT and Deeply Regularized Latent-Space Linear Regression.

It is useful to include OCT measurements when predicting future VF progression in glaucoma patients, especially with short VF series.