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Artificial Intelligence to Aid Glaucoma Diagnosis and Monitoring: State of the Art and New Directions.
Nunez, Roberto; Harris, Alon; Ibrahim, Omar; Keller, James; Wikle, Christopher K; Robinson, Erin; Zukerman, Ryan; Siesky, Brent; Verticchio, Alice; Rowe, Lucas; Guidoboni, Giovanna.
Afiliación
  • Nunez R; Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA.
  • Harris A; Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA.
  • Ibrahim O; Department of Electrical Engineering, Tikrit University, Tikrit P.O. Box 42, Iraq.
  • Keller J; Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA.
  • Wikle CK; Department of Statistic, University of Missouri, Columbia, MO 65211, USA.
  • Robinson E; Department of Social Work, University of Missouri, Columbia, MO 65211, USA.
  • Zukerman R; Department of Ophthalmology, Edward S. Harkness Eye Institute, Columbia University Irving Medical Center, New York-Presbyterian Hospital, New York, NY 10034, USA.
  • Siesky B; Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA.
  • Verticchio A; Department of Ophthalmology, Icahn School of Medicine at Mt. Sinai, New York, NY 10029, USA.
  • Rowe L; Department of Ophthalmology, Indiana University School of Medicine, Indianapolis, IN 46202, USA.
  • Guidoboni G; Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA.
Photonics ; 9(11)2022 Nov.
Article en En | MEDLINE | ID: mdl-36816462
ABSTRACT
Recent developments in the use of artificial intelligence in the diagnosis and monitoring of glaucoma are discussed. To set the context and fix terminology, a brief historic overview of artificial intelligence is provided, along with some fundamentals of statistical modeling. Next, recent applications of artificial intelligence techniques in glaucoma diagnosis and the monitoring of glaucoma progression are reviewed, including the classification of visual field images and the detection of glaucomatous change in retinal nerve fiber layer thickness. Current challenges in the direct application of artificial intelligence to further our understating of this disease are also outlined. The article also discusses how the combined use of mathematical modeling and artificial intelligence may help to address these challenges, along with stronger communication between data scientists and clinicians.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Photonics Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Prognostic_studies Idioma: En Revista: Photonics Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos