EE-Explorer: A Multimodal Artificial Intelligence System for Eye Emergency Triage and Primary Diagnosis.
Am J Ophthalmol
; 252: 253-264, 2023 08.
Article
em En
| MEDLINE
| ID: mdl-37142171
ABSTRACT
PURPOSE:
To develop a multimodal artificial intelligence (AI) system, EE-Explorer, to triage eye emergencies and assist in primary diagnosis using metadata and ocular images.DESIGN:
A diagnostic, cross-sectional, validity and reliability study.METHODS:
EE-Explorer consists of 2 models. The triage model was developed from metadata (events, symptoms, and medical history) and ocular surface images via smartphones from 2038 patients presenting to Zhongshan Ophthalmic Center (ZOC) to output 3 classifications urgent, semiurgent, and nonurgent. The primary diagnostic model was developed from the paired metadata and slitlamp images of 2405 patients from ZOC. Both models were externally tested on 103 participants from 4 other hospitals. A pilot test was conducted in Guangzhou to evaluate the hierarchical referral service pattern assisted by EE-Explorer for unspecialized health care facilities.RESULTS:
A high overall accuracy, as indicated by an area under the receiver operating characteristic curve (AUC) of 0.982 (95% CI, 0.966-0.998), was obtained using the triage model, which outperformed the triage nurses (P < .001). In the primary diagnostic model, the diagnostic classification accuracy (CA) and Hamming loss (HL) in the internal testing were 0.808 (95% CI 0.776-0.840) and 0.016 (95% CI 0.006-0.026), respectively. In the external testing, model performance was robust for both triage (average AUC, 0.988, 95% CI 0.967-1.000) and primary diagnosis (CA, 0.718, 95% CI 0.644-0.792; and HL, 0.023, 95% CI 0.000-0.048). In the pilot test in the hierarchical referral settings, EE-explorer demonstrated consistently robust performance and broad participant acceptance.CONCLUSION:
The EE-Explorer system showed robust performance in both triage and primary diagnosis for ophthalmic emergency patients. EE-Explorer can provide patients with acute ophthalmic symptoms access to remote self-triage and assist in primary diagnosis in unspecialized health care facilities to achieve rapid and effective treatment strategies.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Inteligência Artificial
/
Triagem
Tipo de estudo:
Diagnostic_studies
/
Observational_studies
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Prevalence_studies
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article