Low-Shot Deep Learning of Diabetic Retinopathy With Potential Applications to Address Artificial Intelligence Bias in Retinal Diagnostics and Rare Ophthalmic Diseases.

Burlina, Philippe; Paul, William; Mathew, Philip; Joshi, Neil; Pacheco, Katia D; Bressler, Neil M

Burlina, Philippe; Paul, William; Mathew, Philip; Joshi, Neil; Pacheco, Katia D; Bressler, Neil M.

Afiliación

Burlina P; Applied Physics Laboratory, The Johns Hopkins University, Baltimore, Maryland.
Paul W; Wilmer Eye Institute, Retina Division, The Johns Hopkins University School of Medicine, Baltimore, Maryland.
Mathew P; Malone Center for Engineering in Healthcare, Department of Computer Science, The Johns Hopkins University, Baltimore, Maryland.
Joshi N; Applied Physics Laboratory, The Johns Hopkins University, Baltimore, Maryland.
Pacheco KD; Applied Physics Laboratory, The Johns Hopkins University, Baltimore, Maryland.
Bressler NM; Applied Physics Laboratory, The Johns Hopkins University, Baltimore, Maryland.

JAMA Ophthalmol ; 138(10): 1070-1077, 2020 10 01.

Article en En | MEDLINE | ID: mdl-32880609

Asunto(s)

Algoritmos; Inteligencia Artificial; Aprendizaje Profundo; Retinopatía Diabética/diagnóstico; Redes Neurales de la Computación; Enfermedades Raras/diagnóstico; Estudios Transversales; Femenino; Humanos; Masculino; Curva ROC; Estudios Retrospectivos

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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Algoritmos / Inteligencia Artificial / Redes Neurales de la Computación / Enfermedades Raras / Retinopatía Diabética / Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans / Male Idioma: En Revista: JAMA Ophthalmol Año: 2020 Tipo del documento: Article

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