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Validation of a deep learning system for the detection of diabetic retinopathy in Indigenous Australians.
Chia, Mark A; Hersch, Fred; Sayres, Rory; Bavishi, Pinal; Tiwari, Richa; Keane, Pearse A; Turner, Angus W.
Afiliação
  • Chia MA; Institute of Ophthalmology, University College London, London, UK mark.a.chia@outlook.com.
  • Hersch F; Moorfields Eye Hospital NHS Foundation Trust, London, UK.
  • Sayres R; Lions Outback Vision, Lions Eye Institute, Nedlands, Western Australia, Australia.
  • Bavishi P; Google Health, Palo Alto, California, USA.
  • Tiwari R; Google Health, Palo Alto, California, USA.
  • Keane PA; Google Health, Palo Alto, California, USA.
  • Turner AW; Google Health, Palo Alto, California, USA.
Br J Ophthalmol ; 108(2): 268-273, 2024 01 29.
Article em En | MEDLINE | ID: mdl-36746615
BACKGROUND/AIMS: Deep learning systems (DLSs) for diabetic retinopathy (DR) detection show promising results but can underperform in racial and ethnic minority groups, therefore external validation within these populations is critical for health equity. This study evaluates the performance of a DLS for DR detection among Indigenous Australians, an understudied ethnic group who suffer disproportionately from DR-related blindness. METHODS: We performed a retrospective external validation study comparing the performance of a DLS against a retinal specialist for the detection of more-than-mild DR (mtmDR), vision-threatening DR (vtDR) and all-cause referable DR. The validation set consisted of 1682 consecutive, single-field, macula-centred retinal photographs from 864 patients with diabetes (mean age 54.9 years, 52.4% women) at an Indigenous primary care service in Perth, Australia. Three-person adjudication by a panel of specialists served as the reference standard. RESULTS: For mtmDR detection, sensitivity of the DLS was superior to the retina specialist (98.0% (95% CI, 96.5 to 99.4) vs 87.1% (95% CI, 83.6 to 90.6), McNemar's test p<0.001) with a small reduction in specificity (95.1% (95% CI, 93.6 to 96.4) vs 97.0% (95% CI, 95.9 to 98.0), p=0.006). For vtDR, the DLS's sensitivity was again superior to the human grader (96.2% (95% CI, 93.4 to 98.6) vs 84.4% (95% CI, 79.7 to 89.2), p<0.001) with a slight drop in specificity (95.8% (95% CI, 94.6 to 96.9) vs 97.8% (95% CI, 96.9 to 98.6), p=0.002). For all-cause referable DR, there was a substantial increase in sensitivity (93.7% (95% CI, 91.8 to 95.5) vs 74.4% (95% CI, 71.1 to 77.5), p<0.001) and a smaller reduction in specificity (91.7% (95% CI, 90.0 to 93.3) vs 96.3% (95% CI, 95.2 to 97.4), p<0.001). CONCLUSION: The DLS showed improved sensitivity and similar specificity compared with a retina specialist for DR detection. This demonstrates its potential to support DR screening among Indigenous Australians, an underserved population with a high burden of diabetic eye disease.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Retinopatia Diabética / Aprendizado Profundo / População Australasiana Tipo de estudo: Diagnostic_studies Limite: Female / Humans / Male / Middle aged País/Região como assunto: Oceania Idioma: En Revista: Br J Ophthalmol Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Diabetes Mellitus / Retinopatia Diabética / Aprendizado Profundo / População Australasiana Tipo de estudo: Diagnostic_studies Limite: Female / Humans / Male / Middle aged País/Região como assunto: Oceania Idioma: En Revista: Br J Ophthalmol Ano de publicação: 2024 Tipo de documento: Article