Mariane Melo

Government of the United Kingdom - Moorfields Eye Hospital

London

United Kingdom

  • Government of the United Kingdom - Moorfields Eye Hospital

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A Machine Learning System to Optimise Triage in Adult Ophthalmic Emergency Departments: Development, Temporal/External Validation, Bias and Robustness Analyses

Number of pages: 21 Posted: 12 Jul 2023
Camilo Brandão-de-Resende, Mariane Melo, Elsa Lee, Anish Jindal, Yan Ning Neo, Priyanka Sanghi, Joao Freitas, Paulo Castro, Victor Rosa, Guilherme Valentim, Maria Luisa Higino, Gordon Hay, Pearse Keane, Daniel Vasconcelos-Santos and Alexander Day
University College London - Institute of Ophthalmology, Government of the United Kingdom - Moorfields Eye Hospital, University College London - Institute of Ophthalmology, Government of the United Kingdom - Moorfields Eye Hospital, Government of the United Kingdom - Moorfields Eye Hospital, Government of the United Kingdom - Moorfields Eye Hospital, University of São Paulo (USP), Federal University of Minas Gerais (UFMG), Federal University of Minas Gerais (UFMG), Federal University of Minas Gerais (UFMG), Federal University of Minas Gerais (UFMG), Government of the United Kingdom - Moorfields Eye Hospital, Government of the United Kingdom - Moorfields Eye Hospital, Federal University of Minas Gerais (UFMG) and Government of the United Kingdom - Moorfields Eye Hospital
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Machine Learning, Artificial Intelligence, Ophthalmology, Triage, Emergency, Digital Health