Cargando…

Artificial Intelligence for Diabetic Retinopathy Screening Using Color Retinal Photographs: From Development to Deployment

Diabetic retinopathy (DR), a leading cause of preventable blindness, is expected to remain a growing health burden worldwide. Screening to detect early sight-threatening lesions of DR can reduce the burden of vision loss; nevertheless, the process requires intensive manual labor and extensive resour...

Descripción completa

Detalles Bibliográficos
Autores principales:	Grzybowski, Andrzej, Singhanetr, Panisa, Nanegrungsunk, Onnisa, Ruamviboonsuk, Paisan
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Springer Healthcare 2023
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164194/ https://www.ncbi.nlm.nih.gov/pubmed/36862308 http://dx.doi.org/10.1007/s40123-023-00691-3

Ejemplares similares

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

Potential Ocular Biomarkers for Early Detection of Alzheimer’s Disease and Their Roles in Artificial Intelligence Studies
por: Chaitanuwong, Pareena, et al.
Publicado: (2023)

Investigating public behavior with artificial intelligence-assisted detection of face mask wearing during the COVID-19 pandemic
por: Seresirikachorn, Kasem, et al.
Publicado: (2023)

Ophthalmic imaging in diabetic retinopathy: A review
por: Nanegrungsunk, Onnisa, et al.
Publicado: (2022)

Influence of Different Types of Retinal Cameras on the Performance of Deep Learning Algorithms in Diabetic Retinopathy Screening
por: Srinivasan, Ramyaa, et al.
Publicado: (2022)

The Roles of Vitamins in Diabetic Retinopathy: A Narrative Review
por: Ruamviboonsuk, Varis, et al.
Publicado: (2022)

Color vision restrictions for medical school admission: a discussion on regulations in ASEAN countries compared to countries across the world
por: Tan, Ting Fang, et al.
Publicado: (2023)

New frontiers of retinal therapeutic intervention: a critical analysis of novel approaches
por: Nanegrungsunk, Onnisa, et al.
Publicado: (2022)

Analysis and Comparison of Two Artificial Intelligence Diabetic Retinopathy Screening Algorithms in a Pilot Study: IDx-DR and Retinalyze
por: Grzybowski, Andrzej, et al.
Publicado: (2021)

The Classification of Common Macular Diseases Using Deep Learning on Optical Coherence Tomography Images with and without Prior Automated Segmentation
por: Kaothanthong, Natsuda, et al.
Publicado: (2023)

Capacity building in screening and treatment of diabetic retinopathy in Asia-Pacific region
por: Silpa-archa, Sukhum, et al.
Publicado: (2021)

Longitudinal Screening for Diabetic Retinopathy in a Nationwide Screening Program: Comparing Deep Learning and Human Graders
por: Limwattanayingyong, Jirawut, et al.
Publicado: (2020)

Microbial contamination of multiple-dose preservative-free hospital ophthalmic preparations in a tertiary care hospital
por: Chantra, Somporn, et al.
Publicado: (2022)

Systems medicine and artificial intelligence in retinal disease
por: Zeitz, Oliver, et al.
Publicado: (2022)

The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy
por: Pieczynski, Janusz, et al.
Publicado: (2021)

Artificial intelligence-based detection of epimacular membrane from color fundus photographs
por: Shao, Enhua, et al.
Publicado: (2021)

Patient and provider perspectives on barriers to screening for diabetic retinopathy: an exploratory study from southern India
por: Kumar, Shuba, et al.
Publicado: (2020)

The Association Between Environmental and Social Factors and Myopia: A Review of Evidence From COVID-19 Pandemic
por: Limwattanayingyong, Jirawut, et al.
Publicado: (2022)

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

Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus
por: Chou, Yu-Bai, et al.
Publicado: (2023)

Diagnostic Accuracy of Automated Diabetic Retinopathy Image Assessment Softwares: IDx-DR and Medios Artificial Intelligence
por: Grzybowski, Andrzej, et al.
Publicado: (2023)

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

The impact of artificial intelligence on retinal disease management: Vision Academy retinal expert consensus
por: Danese, Carla, et al.
Publicado: (2023)

Cost-Utility Analysis of Deep Learning and Trained Human Graders for Diabetic Retinopathy Screening in a Nationwide Program
por: Srisubat, Attasit, et al.
Publicado: (2023)

Artificial intelligence for diabetic retinopathy
por: Li, Sicong, 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)

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

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

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

Correlation between change in central subfield thickness and change in visual acuity in macular edema due to retinal vein occlusion: post hoc analysis of COPERNICUS, GALILEO, and VIBRANT
por: Gu, Sophie Z., et al.
Publicado: (2022)

Which Color Channel Is Better for Diagnosing Retinal Diseases Automatically in Color Fundus Photographs?
por: Biswas, Sangeeta, et al.
Publicado: (2022)

An Artificial-Intelligence–Based Automated Grading and Lesions Segmentation System for Myopic Maculopathy Based on Color Fundus Photographs
por: Tang, Jia, et al.
Publicado: (2022)

Patient, family member, and health care provider perspective on barriers and facilitators to diabetic retinopathy screening in Thailand: A qualitative study
por: Kumar, Geetha, et al.
Publicado: (2023)

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

Accuracy of Artificial Intelligence-Based Photographic Detection of Gingivitis
por: Chau, Reinhard Chun Wang, et al.
Publicado: (2023)

Characteristics of road traffic mortality and distribution of healthcare resources in Thailand
por: Seresirikachorn, Kasem, et al.
Publicado: (2022)

The Evolution of Diabetic Retinopathy Screening Programmes: A Chronology of Retinal Photography from 35 mm Slides to Artificial Intelligence
por: Huemer, Josef, et al.
Publicado: (2020)

Automatic Detection of Diabetic Retinopathy in Retinal Fundus Photographs Based on Deep Learning Algorithm
por: Li, Feng, et al.
Publicado: (2019)

Photographs in Natural Colors
Publicado: (1881)

Cannot write session to /tmp/vufind_sessions/sess_o4fv8pocinmgn4na221pm9n6jd