Predicting visual acuity outcomes in nAMD, RVO and DME by machine learning

被引：0
|
作者：
Sadeghipour, Amir [1 ]
Waldstein, Sebastian M. [1 ]
Gerendas, Bianca S. [1 ]
Osborne, Aaron [2 ]
Schmidt-Erfurth, Ursula [1 ]
机构：
[1] Med Univ Vienna, Dept Ophthalmol, Vienna, Austria
[2] Genentech Inc, San Francisco, CA 94080 USA
来源：
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE | 2018年 / 59卷 / 09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：
1738
引用
收藏
页数：7
相关论文
共 50 条
  • [21] Machine Learning in Predicting Poor Glycemic Outcomes
    Alquadan, Hammam
    Siminerio, Linda M.
    Krall, Jodi T.
    Ng, Jason
    DIABETES, 2020, 69
  • [22] Value of machine learning in predicting TAVI outcomes
    R. R. Lopes
    M. S. van Mourik
    E. V. Schaft
    L. A. Ramos
    J. Baan Jr.
    J. Vendrik
    B. A. J. M. de Mol
    M. M. Vis
    H. A. Marquering
    Netherlands Heart Journal, 2019, 27 : 443 - 450
  • [23] Machine Learning: A Novel Approach for Predicting Visual Outcomes and Factors Affecting it in Patients with Pituitary Adenomas
    Shah, Shreykumar Pravinchandra
    Ranjith, G.
    Narendran, Meghana
    Patel, Biren Khimji
    Gowda, Arun
    George, Tobin
    Easwer, H., V
    Nair, Prakash
    NEUROLOGY INDIA, 2025, 73 (01) : 102 - 109
  • [24] A Probabilistic Forecast of 12 Month Visual Outcomes of nAMD
    Vuong Nguyen
    Teo, Kelvin
    Simpson, Judy
    Daien, Vincent
    Barthelmes, Daniel
    Gillies, Mark C.
    Walton, Richard
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2018, 59 (09)
  • [25] Predicting visual acuity from the structure of visual cortex
    Srinivasan, Shyam
    Carlo, C. Nikoosh
    Stevens, Charles F.
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2015, 112 (25) : 7815 - 7820
  • [26] The impact of COVID-19 on visual acuity for nAMD patients treated with aflibercept in the UK
    Bailey, Clare
    Gruszka-Goh, Marta Helena
    Lotery, Andrew J.
    Chhabra, Romi
    Eleftheriadis, Haralabos
    Ghanchi, Faruque
    Jones, Colin
    Scanlon, Peter H.
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 2022, 63 (07)
  • [27] Management of Patients With DME With Good Visual Acuity in Routine Clinical Practice
    Hentati, Firas
    Melo, Alline G. R.
    Greenlee, Tyler E.
    Muste, Justin
    Chen, Andrew X.
    Conti, Thais F.
    Hom, Grant L.
    Singh, Rishi P.
    OPHTHALMIC SURGERY LASERS & IMAGING RETINA, 2021, 52 (05): : 247 - 256
  • [28] Machine Learning to Predict Visual Acuity Outcomes from Imaging Biomarkers in Neovascular Age-Related Macular Degeneration
    Waldstein, Sebastian
    Bogunovic, Hrvoje
    Sadeghipour, Amir
    Schlegl, Thomas
    Gerendas, Bianca S.
    Osborne, Aaron
    Schmidt-Erfurth, Ursula
    OPHTHALMOLOGICA, 2016, 236 : 3 - 3
  • [29] Second-year visual acuity outcomes of nAMD patients treated with aflibercept: data analysis from the UK Aflibercept Users Group
    H Almuhtaseb
    R L Johnston
    J S Talks
    A J Lotery
    Eye, 2017, 31 : 1582 - 1588
  • [30] Predicting outcomes of pelvic exenteration using machine learning
    Dudurych, I.
    Kelly, M. E.
    Aalbers, A. G. J.
    Aziz, N. Abdul
    Abecasis, N.
    Abraham-Nordling, M.
    Akiyoshi, T.
    Alberda, W.
    Albert, M.
    Andric, M.
    Angenete, E.
    Antoniou, A.
    Auer, R.
    Austin, K. K.
    Aziz, O.
    Baker, R. P.
    Bali, M.
    Baseckas, G.
    Bebington, B.
    Bedford, M.
    Bednarski, B. K.
    Beets, G. L.
    Berg, P. L.
    Beynon, J.
    Biondo, S.
    Boyle, K.
    Bordeianou, L.
    Bremers, A. B.
    Brunner, M.
    Buchwald, P.
    Bui, A.
    Burgess, A.
    Burger, J. W. A.
    Burling, D.
    Burns, E.
    Campain, N.
    Carvalhal, S.
    Castro, L.
    Caycedo-Marulanda, A.
    Chan, K. K. L.
    Chang, G. J.
    Chew, M. H.
    Chok, A. K.
    Chong, P.
    Christensen, H. K.
    Clouston, H.
    Codd, M.
    Collins, D.
    Colquhoun, A. J.
    Corr, A.
    COLORECTAL DISEASE, 2020, 22 (12) : 1933 - 1940
12345