A Novel Method to Improve Inter-Clinician Variation in the Diagnosis of Retinopathy of Prematurity Using Machine Learning.

Nisha, K L; Ganapathy, Sreelekha; Puthumangalathu Savithri, Sathidevi; Idaguri, Madhu; Mohanachandran, Poornima; Vinekar, Anand; Chandra, Parijat; Kulkarni, Sucheta; Dogra, Mangat

Nisha, K L; Ganapathy, Sreelekha; Puthumangalathu Savithri, Sathidevi; Idaguri, Madhu; Mohanachandran, Poornima; Vinekar, Anand; Chandra, Parijat; Kulkarni, Sucheta; Dogra, Mangat.

Afiliación

Nisha KL; National Institute of Technology Calicut, Calicut, India.
Ganapathy S; National Institute of Technology Calicut, Calicut, India.
Puthumangalathu Savithri S; National Institute of Technology Calicut, Calicut, India.
Idaguri M; ekLakshya Academy LLP, Hubli, India.
Mohanachandran P; ekLakshya Academy LLP, Hubli, India.
Vinekar A; Narayana Nethralaya Eye Institute, Bangalore, India.
Chandra P; Dr R. P. Centre for Ophthalmic Sciences, AIIMS, New Delhi, India.
Kulkarni S; PBMA's H V Desai Eye Hospital, Pune, India.
Dogra M; Advanced Eye Centre, Postgraduate Institute of Medical Education and Research, Chandigarh, India.

Curr Eye Res ; 48(1): 60-69, 2023 01.

Article en En | MEDLINE | ID: mdl-36322485

Asunto(s)

Retinopatía de la Prematuridad; Recién Nacido; Lactante; Humanos; Retinopatía de la Prematuridad/diagnóstico; Recien Nacido Prematuro; Aprendizaje Automático; Fotograbar; Variaciones Dependientes del Observador; Reproducibilidad de los Resultados

Palabras clave

Inter-clinician variation; feature selection; machine learning; plus disease; retinopathy of prematurity

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Retinopatía de la Prematuridad Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Humans / Infant / Newborn Idioma: En Revista: Curr Eye Res Año: 2023 Tipo del documento: Article País de afiliación: India

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