Artificial intelligence methods in diagnosis of retinoblastoma based on fundus imaging: a systematic review and meta-analysis.

Journal: Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PMID: 39289309

Abstract

BACKGROUND: Artificial intelligence (AI) algorithms for the detection of retinoblastoma (RB) by fundus image analysis have been proposed as a potentially effective technique to facilitate diagnosis and screening programs. However, doubts remain about the accuracy of the technique, the best type of AI for this situation, and its feasibility for everyday use. Therefore, we performed a systematic review and meta-analysis to evaluate this issue.

Authors

  • Rian Vilar Lima
    Department of Medicine, University of Fortaleza, Av. Washington Soares, 1321 - Edson Queiroz, Fortaleza - CE, Ceará, 60811-905, Brazil. rianvilar@edu.unifor.br.
  • Mateus Pimenta Arruda
    Penido Burnier Institute, São Paulo, Brazil.
  • Maria Carolina Rocha Muniz
    Department of Medicine, University of Fortaleza, Av. Washington Soares, 1321 - Edson Queiroz, Fortaleza - CE, Ceará, 60811-905, Brazil.
  • Helvécio Neves Feitosa Filho
    Department of Medicine, University of Fortaleza, Av. Washington Soares, 1321 - Edson Queiroz, Fortaleza - CE, Ceará, 60811-905, Brazil.
  • Daiane Memória Ribeiro Ferrerira
    Pediatric Cancer Center, Fortaleza, Brazil.
  • Samuel Montenegro Pereira
    Pediatric Cancer Center, Fortaleza, Brazil.

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