A case study in applying artificial intelligence-based named entity recognition to develop an automated ophthalmic disease registry.

Macri, Carmelo Z; Teoh, Sheng Chieh; Bacchi, Stephen; Tan, Ian; Casson, Robert; Sun, Michelle T; Selva, Dinesh; Chan, WengOnn

Macri, Carmelo Z; Teoh, Sheng Chieh; Bacchi, Stephen; Tan, Ian; Casson, Robert; Sun, Michelle T; Selva, Dinesh; Chan, WengOnn.

Afiliación

Macri CZ; Discipline of Ophthalmology and Visual Sciences, The University of Adelaide, Adelaide, South Australia, Australia. carmelo.macri@adelaide.edu.au.
Teoh SC; Department of Ophthalmology, The Royal Adelaide Hospital, Adelaide, South Australia, Australia. carmelo.macri@adelaide.edu.au.
Bacchi S; Department of Ophthalmology, The Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Tan I; Discipline of Ophthalmology and Visual Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
Casson R; Department of Ophthalmology, The Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Sun MT; Department of Ophthalmology, The Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Selva D; Discipline of Ophthalmology and Visual Sciences, The University of Adelaide, Adelaide, South Australia, Australia.
Chan W; Department of Ophthalmology, The Royal Adelaide Hospital, Adelaide, South Australia, Australia.

Graefes Arch Clin Exp Ophthalmol ; 261(11): 3335-3344, 2023 Nov.

Article en En | MEDLINE | ID: mdl-37535181

Palabras clave

Application; Artificial intelligence; Case study; Electronic health records; Named entity recognition; Registry; Tool

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Graefes Arch Clin Exp Ophthalmol Año: 2023 Tipo del documento: Article País de afiliación: Australia

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