Cargando…

Clinical validation of an artificial intelligence-based diabetic retinopathy screening tool for a national health system

OBJECTIVE: To evaluate the accuracy and validity of an automated diabetic retinopathy (DR) screening tool (DART, TeleDx, Santiago, Chile) that uses artificial intelligence to analyze ocular fundus photographs for potential implementation in the national Chilean DR screening programme. METHOD: This w...

Descripción completa

Detalles Bibliográficos
Autores principales:	Arenas-Cavalli, José Tomás, Abarca, Ignacio, Rojas-Contreras, Maximiliano, Bernuy, Fernando, Donoso, Rodrigo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8727616/ https://www.ncbi.nlm.nih.gov/pubmed/33432168 http://dx.doi.org/10.1038/s41433-020-01366-0

Ejemplares similares

Correction: Clinical validation of an artificial intelligence-based diabetic retinopathy screening tool for a national health system
por: Arenas-Cavalli, José Tomás, et al.
Publicado: (2021)

Development and validation of an artificial intelligence based screening tool for detection of retinopathy of prematurity in a South Indian population
por: Rao, Divya Parthasarathy, et al.
Publicado: (2023)

Artificial intelligence for diabetic retinopathy screening: beyond diagnostic accuracy
por: Malerbi, Fernando Korn
Publicado: (2022)

Feasibility of screening for diabetic retinopathy using artificial intelligence, Brazil
por: Malerbi, Fernando Korn, et al.
Publicado: (2022)

Artificial intelligence for diabetic retinopathy
por: Li, Sicong, et al.
Publicado: (2022)

Validation of Artificial Intelligence Algorithm in the Detection and Staging of Diabetic Retinopathy through Fundus Photography: An Automated Tool for Detection and Grading of Diabetic Retinopathy
por: Pawar, Bhargavi, et al.
Publicado: (2021)

Artificial intelligence for telemedicine diabetic retinopathy screening: a review
por: Nakayama, Luis Filipe, et al.
Publicado: (2023)

Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy
por: Huang, Xuan, et al.
Publicado: (2022)

Artificial Intelligence in Retinopathy of Prematurity Diagnosis
por: Scruggs, Brittni A., et al.
Publicado: (2020)

Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy
por: Tsai, Meng-Ju, et al.
Publicado: (2022)

Application Research of Artificial Intelligence Screening System for Diabetic Retinopathy
por: Wang, Yuwen, et al.
Publicado: (2022)

Using artificial intelligence for diabetic retinopathy screening: Policy implications
por: Raman, Rajiv, et al.
Publicado: (2021)

Cost-effectiveness of artificial intelligence screening for diabetic retinopathy in rural China
por: Huang, Xiao-Mei, et al.
Publicado: (2022)

Evaluation of an Artificial Intelligence System for Retinopathy of Prematurity Screening in Nepal and Mongolia
por: Cole, Emily, et al.
Publicado: (2022)

Prospective studies on artificial intelligence (AI)-based diabetic retinopathy screening
por: Nanegrungsunk, Onnisa, et al.
Publicado: (2022)

Single retinal image for diabetic retinopathy screening: performance of a handheld device with embedded artificial intelligence
por: Penha, Fernando Marcondes, et al.
Publicado: (2023)

Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy – Artificial intelligence versus clinician for screening
por: Shah, Payal, et al.
Publicado: (2020)

Multicenter, Head-to-Head, Real-World Validation Study of Seven Automated Artificial Intelligence Diabetic Retinopathy Screening Systems
por: Lee, Aaron Y., et al.
Publicado: (2021)

Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening
por: Xie, Yuchen, et al.
Publicado: (2020)

Artificial Intelligence Tools for Refining Lung Cancer Screening
por: Espinoza, J. Luis, et al.
Publicado: (2020)

Artificial intelligence in diabetic retinopathy: A natural step to the future
por: Padhy, Srikanta Kumar, et al.
Publicado: (2019)

An overview of artificial intelligence in diabetic retinopathy and other ocular diseases
por: Sheng, Bin, et al.
Publicado: (2022)

Artificial Intelligence-Based Teleopthalmology Application for Diagnosis of Diabetics Retinopathy
Publicado: (2022)

Diabetic and Hypertensive Retinopathy Screening in Fundus Images Using Artificially Intelligent Shallow Architectures
por: Arsalan, Muhammad, et al.
Publicado: (2021)

Artificial Intelligence Improves Patient Follow-Up in a Diabetic Retinopathy Screening Program
por: Dow, Eliot R, et al.
Publicado: (2023)

Development and validation pathways of artificial intelligence tools evaluated in randomised clinical trials
por: Siontis, George C M, et al.
Publicado: (2021)

Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study
por: Zhang, Yifei, et al.
Publicado: (2020)

Screening for Diabetic Retinopathy in Endocrinology Clinics by Using Handheld Cameras and Applying Artificial Intelligence Algorithms
por: Dvey-Aharon, Zack, et al.
Publicado: (2021)

Commentary: Smartphone imaging integrated with offline artificial intelligence – A boon for the screening of diabetic retinopathy
por: Ramasamy, Kim, et al.
Publicado: (2021)

Is Artificial Intelligence the Cost-Saving Lens to Diabetic Retinopathy Screening in Low- and Middle-Income Countries?
por: Rizvi, Anza, et al.
Publicado: (2023)

Planning an artificial intelligence diabetic retinopathy screening program: a human-centered design approach
por: Scanzera, Angelica C., et al.
Publicado: (2023)

Artificial Intelligence for Diabetic Retinopathy Screening Using Color Retinal Photographs: From Development to Deployment
por: Grzybowski, Andrzej, et al.
Publicado: (2023)

Diabetic retinopathy screening and treatment through the Brazilian National Health Insurance
por: Fernandes, Arthur Gustavo, et al.
Publicado: (2022)

Evaluating the Viability of a Smartphone-Based Annotation Tool for Faster and Accurate Image Labelling for Artificial Intelligence in Diabetic Retinopathy
por: Morya, Arvind Kumar, et al.
Publicado: (2021)

Evaluation of Artificial Intelligence–Based Grading of Diabetic Retinopathy in Primary Care
por: Kanagasingam, Yogesan, et al.
Publicado: (2018)

Artificial intelligence tools for cyber attribution
por: Nunes, Eric, et al.
Publicado: (2018)

Artificial intelligence: tools, techniques, and applications
por: Eisenstadt, Marc, et al.
Publicado: (1984)

Pathways to breast cancer screening artificial intelligence algorithm validation
por: Lee, Christoph I., et al.
Publicado: (2019)

Development and Validation of an Observational Game Analysis Tool with Artificial Intelligence for Handball: Handball.ai
por: Marquina, Moises, et al.
Publicado: (2023)

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients
por: Heydon, Peter, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_dme1s6b1t7pnol0fml8lmpbtg7