@inproceedings{558acfe719b741d8b6b7f6375f8cdfed,
title = "VF2VF: Improving Precision while Maintaining Accuracy",
abstract = "Visual Field (VF), a measurement of retinal function, is one of the most important references in modern glaucoma diagnosis and treatment. While VF is a typical physical-psychological measurement, the results are often imprecise. How to improve measurement accuracy is always one of the most significant issues in clinical practice. This study proposes a VF2VF training method based on the assumption that the pattern of multiple VF measurements in a short period does not change, and designs a neural network to transform the VF measurements. We analyze the VFs after transformation through experiments. Experiments show that the training method of VF2VF can significantly improve the precision while maintaining the accuracy of original VFs. Besides, the VFs after transformation achieve a significant performance improvement in downstream deterioration detection tasks. When the false positive rate is 5\%, the Hit Rate increases by 20\%. And the transformed VFs can give a warning 1.8 times ahead of the original VFs.",
keywords = "accuracy, deterioration detection, glaucoma, precision, visual field",
author = "Zhenyu Zhang and Xuebin Chen and Haogang Zhu",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Big Data, Big Data 2022 ; Conference date: 17-12-2022 Through 20-12-2022",
year = "2022",
doi = "10.1109/BigData55660.2022.10020491",
language = "英语",
series = "Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5388--5394",
editor = "Shusaku Tsumoto and Yukio Ohsawa and Lei Chen and \{Van den Poel\}, Dirk and Xiaohua Hu and Yoichi Motomura and Takuya Takagi and Lingfei Wu and Ying Xie and Akihiro Abe and Vijay Raghavan",
booktitle = "Proceedings - 2022 IEEE International Conference on Big Data, Big Data 2022",
address = "美国",
}