Prediction of Geographic Atrophy Enlargement using Various Deep Learning Approaches

被引：0
|
作者：
Domalpally, Amitha [1 ,2 ]
Slater, Robert [1 ]
Banghart, Mark [1 ]
Channa, Roomasa [1 ]
Fong, Donald S. [3 ]
Blodi, Barbara A. [2 ]
机构：
[1] Univ Wisconsin Madison, Dept Ophthalmol & Visual Sci, EYE Unit, Madison, WI USA
[2] Univ Wisconsin Madison, Dept Ophthalmol & Visual Sci, Wisconsin Reading Ctr, Madison, WI USA
[3] Annexon Biosci, Brisbane, CA USA
来源：
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE | 2023年 / 64卷 / 08期
关键词：
D O I：
暂无
中图分类号：
R77 [眼科学];
学科分类号：
100212 ;
摘要：
265
引用
收藏
页数：3
相关论文
共 50 条
  • [21] Deep Learning-Based Prediction of Individual Geographic Atrophy Progression from a Single Baseline OCT
    Mai, Julia
    Lachinov, Dmitrii
    Reiter, Gregor S.
    Riedl, Sophie
    Grechenig, Christoph
    Bogunovic, Hrvoje
    Schmidt-Erfurth, Ursula
    OPHTHALMOLOGY SCIENCE, 2024, 4 (04):
  • [22] Training Size Effect on Deep Learning Models for Geographic Atrophy
    Slater, Robert
    Banghart, Mark
    Channa, Roomasa
    Blodi, Barbara A.
    Fong, Donald S.
    Domalpally, Amitha
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2023, 64 (08)
  • [23] Estimating Uncertainty of Geographic Atrophy Segmentations with Bayesian Deep Learning
    Spaide, Theodore
    Rajesh, Anand E.
    Gim, Nayoon
    Blazes, Marian
    Lee, Cecilia S.
    Macivannan, Niranchana
    Lee, Gary
    Lewis, Warren
    Salehi, Ali
    de Sisternes, Luis
    Herrera, Gissel
    Shen, Mengxi
    Gregori, Giovanni
    Rosenfeld, Philip J.
    Pramil, Varsha
    Waheed, Nadia
    Wu, Yue
    Zhang, Qinqin
    Lee, Aaron Y.
    OPHTHALMOLOGY SCIENCE, 2025, 5 (01):
  • [24] Quantifying Uncertainty of Deep Learning Models for the Segmentation of Geographic Atrophy
    Spaide, Theodore
    Owen, Julia
    De Sisternes, Luis
    Lewis, Warren
    Manivannan, Niranchana
    Pramil, Varsha
    Sheikh, Harris Asad
    Waheed, Nadia K.
    Lee, Cecilia S.
    Lee, Aaron Y.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2023, 64 (08)
  • [25] Structural Analysis and Prediction of Hematotoxicity Using Deep Learning Approaches
    Long, Teng-Zhi
    Shi, Shao-Hua
    Liu, Shao
    Lu, Ai-Ping
    Liu, Zhao-Qian
    Li, Min
    Hou, Ting-Jun
    Cao, Dong-Sheng
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2023, 63 (01) : 111 - 125
  • [26] Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier
    Treder, Maximilian
    Lauermann, Jost Lennart
    Eter, Nicole
    GRAEFES ARCHIVE FOR CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY, 2018, 256 (11) : 2053 - 2060
  • [27] Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier
    Maximilian Treder
    Jost Lennart Lauermann
    Nicole Eter
    Graefe's Archive for Clinical and Experimental Ophthalmology, 2018, 256 : 2053 - 2060
  • [28] OCT Minimum Intensity as a Predictor of Geographic Atrophy Enlargement
    Stetson, Paul
    Yehoshua, Zohar
    Garcia Filho, Carlos Alexandre
    Gregori, Giovanni
    Rosenfeld, Philip
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2013, 54 (15)
  • [29] OCT Minimum Intensity as a Predictor of Geographic Atrophy Enlargement
    Stetson, Paul F.
    Yehoshua, Zohar
    Garcia Filho, Carlos Alexandre A.
    Nunes, Renata Portella
    Gregori, Giovanni
    Rosenfeld, Philip J.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2014, 55 (02) : 792 - 800
  • [30] In silico prediction of hERG blockers using machine learning and deep learning approaches
    Chen, Yuanting
    Yu, Xinxin
    Li, Weihua
    Tang, Yun
    Liu, Guixia
    JOURNAL OF APPLIED TOXICOLOGY, 2023, 43 (10) : 1462 - 1475
12345