Published on in Vol 9, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27363, first published .
Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review

Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review

Machine Learning Algorithms to Detect Subclinical Keratoconus: Systematic Review

Journals

  1. Kang L, Ballouz D, Woodward M. Artificial intelligence and corneal diseases. Current Opinion in Ophthalmology 2022;33(5):407 View
  2. Ambrósio R, Machado A, Leão E, Lyra J, Salomão M, Esporcatte L, da Fonseca Filho J, Ferreira-Meneses E, Sena N, Haddad J, Costa Neto A, de Almeida G, Roberts C, Elsheikh A, Vinciguerra R, Vinciguerra P, Bühren J, Kohnen T, Kezirian G, Hafezi F, Hafezi N, Torres-Netto E, Lu N, Kang D, Kermani O, Koh S, Padmanabhan P, Taneri S, Trattler W, Gualdi L, Salgado-Borges J, Faria-Correia F, Flockerzi E, Seitz B, Jhanji V, Chan T, Baptista P, Reinstein D, Archer T, Rocha K, Waring G, Krueger R, Dupps W, Khoramnia R, Hashemi H, Asgari S, Momeni-Moghaddam H, Zarei-Ghanavati S, Shetty R, Khamar P, Belin M, Lopes B. Optimized Artificial Intelligence for Enhanced Ectasia Detection Using Scheimpflug-Based Corneal Tomography and Biomechanical Data. American Journal of Ophthalmology 2023;251:126 View
  3. Fassbind B, Langenbucher A, Streich A. Automated cornea diagnosis using deep convolutional neural networks based on cornea topography maps. Scientific Reports 2023;13(1) View
  4. Al-Timemy A, Alzubaidi L, Mosa Z, Abdelmotaal H, Ghaeb N, Lavric A, Hazarbassanov R, Takahashi H, Gu Y, Yousefi S. A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning. Diagnostics 2023;13(10):1689 View
  5. Kolasa K, Admassu B, Hołownia-Voloskova M, Kędzior K, Poirrier J, Perni S. Systematic reviews of machine learning in healthcare: a literature review. Expert Review of Pharmacoeconomics & Outcomes Research 2024;24(1):63 View
  6. Deshmukh R, Ong Z, Rampat R, Alió del Barrio J, Barua A, Ang M, Mehta J, Said D, Dua H, Ambrósio R, Ting D. Management of keratoconus: an updated review. Frontiers in Medicine 2023;10 View
  7. Mehdizadeh Dastjerdi O, Bakhtiarnia M, Yazdchi M, Maghooli K, Farokhi F, Jadidi K. Ocular condition prognosis in Keratoconus patients after corneal ring implantation using artificial neural networks. Heliyon 2023;9(9):e19411 View
  8. Liu Y, Shen D, Wang H, Qi M, Zeng Q. Development and validation to predict visual acuity and keratometry two years after corneal crosslinking with progressive keratoconus by machine learning. Frontiers in Medicine 2023;10 View
  9. Price L, Larkin D. Diagnosis and management of keratoconus in the paediatric age group: a review of current evidence. Eye 2023;37(18):3718 View
  10. Chen X, Tan Z, Huo Y, Song J, Xu Q, Yang C, Jhanji V, Li J, Hou J, Zou H, Ali Khan G, Alzogool M, Wang R, Wang Y. Localized Corneal Biomechanical Alteration Detected In Early Keratoconus Based on Corneal Deformation Using Artificial Intelligence. Asia-Pacific Journal of Ophthalmology 2023;12(6):574 View
  11. Afifah A, Syafira F, Afladhanti P, Dharmawidiarini D. Artificial intelligence as diagnostic modality for keratoconus: A systematic review and meta-analysis. Journal of Taibah University Medical Sciences 2024;19(2):296 View
  12. Fujinami-Yokokawa Y, Joo K, Liu X, Tsunoda K, Kondo M, Ahn S, Robson A, Naka I, Ohashi J, Li H, Yang L, Arno G, Pontikos N, Park K, Michaelides M, Tachimori H, Miyata H, Sui R, Woo S, Fujinami K. Distinct Clinical Effects of Two RP1L1 Hotspots in East Asian Patients With Occult Macular Dystrophy (Miyake Disease): EAOMD Report 4. Investigative Opthalmology & Visual Science 2024;65(1):41 View