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Perspective June 2021

Impact of Artificial Intelligence on Medical Education in Ophthalmology

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Nita G. Valikodath; Emily Cole; Daniel S. W. Ting; J. Peter Campbell; Louis R. Pasquale; Michael F. Chiang; R. V. Paul Chan; on behalf of the American Academy of Ophthalmology Task Force on Artificial Intelligence
TAGS: artificial intelligence, education, medical, ophthalmology, physicians
Trans. Vis. Sci. Tech.. 2021; 10(7):14. doi: https://doi.org/10.1167/tvst.10.7.14

Perspective March 2021

Artificial Intelligence to Reduce Ocular Health Disparities: Moving From Concept to Implementation

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John P. Campbell; Ciku Mathenge; Hunter Cherwek; Konstantinos Balaskas; Louis R. Pasquale; Pearse A. Keane; Michael F. Chiang; on behalf of the American Academy of Ophthalmology Task Force on Artificial Intelligence
TAGS: artificial intelligence, blindness, diabetic retinopathy, health disparity, implementation science, ophthalmology, screening, technology, glaucoma, refractive errors
Trans. Vis. Sci. Tech.. 2021; 10(3):19. doi: https://doi.org/10.1167/tvst.10.3.19

Special Issue August 2020

Current Challenges and Barriers to Real-World Artificial Intelligence Adoption for the Healthcare System, Provider, and the Patient

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Rishi P. Singh; Grant L. Hom; Michael D. Abramoff; J. Peter Campbell; Michael F. Chiang; on behalf of the AAO Task Force on Artificial Intelligence
TAGS: artificial intelligence, health care systems, technology, eye, ophthalmology
Trans. Vis. Sci. Tech.. 2020; 9(2):45. doi: https://doi.org/10.1167/tvst.9.2.45

Articles July 2020

Ranibizumab Population Pharmacokinetics and Free VEGF Pharmacodynamics in Preterm Infants With Retinopathy of Prematurity in the RAINBOW Trial

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Matthew Fidler; Brian W. Fleck; Andreas Stahl; Neil Marlow; James E. Chastain; Jun Li; Domenico Lepore; James D. Reynolds; Michael F. Chiang; Alistair R. Fielder; on behalf of the RAINBOW study group
TAGS: infant, ranibizumab, vascular endothelial growth factor a, infant, premature, retinopathy of prematurity, pharmacodynamics
Trans. Vis. Sci. Tech.. 2020; 9(8):43. doi: https://doi.org/10.1167/tvst.9.8.43

Includes: Supplemental Content

Special Issue July 2020

Protecting Data Privacy in the Age of AI-Enabled Ophthalmology

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Elysse Tom; Pearse A. Keane; Marian Blazes; Louis R. Pasquale; Michael F. Chiang; Aaron Y. Lee; Cecilia S. Lee; and AAO Artificial Intelligence Task Force
TAGS: ophthalmology, privacy, datasets
Trans. Vis. Sci. Tech.. 2020; 9(2):36. doi: https://doi.org/10.1167/tvst.9.2.36

ARVO Annual Meeting Abstract June 2020

Cost-Utility Analyses of Artificial Intelligence, Telemedicine, and Standard Ophthalmoscopy for Retinopathy of Prematurity Screening

Steven L. Morrison; J. Peter Campbell; Kemal Sonmez; Susan Ostmo; Neal Wallace; Thuan Nguyen; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2192. doi:

ARVO Annual Meeting Abstract June 2020

Characterization of response to treatment in infants with retinopathy of prematurity in the ROPE-SOS trial in rural India

Abdullah Memon; Nita Valikodath; Emily Cole; Tala Al-Khaled; Rawan Allozi Rupnow; Joelle Hallak; J. Peter Campbell; Michael F. Chiang; Parag Shah; Narendran Venkatapathy; Robison Vernon Paul Chan

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2196. doi:

ARVO Annual Meeting Abstract June 2020

Utility of an automated deep learning tool in a low-income country for retinopathy of prematurity

Nita Valikodath; Emily Cole; Tala Al-Khaled; Sanyam Bajimaya; Sagun K.C.; Asha Basnyat; Dale Davis; Nick Kourgialis; Eli Pradhan; Praveer Singh; Jayashree Kalpathy-Cramer; Michael F. Chiang; J. Peter Campbell; Robison Vernon Paul Chan

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1637. doi:

ARVO Annual Meeting Abstract June 2020

Retinal Fundus Image Generation in Retinopathy of Prematurity Using Autoregressive Generative Models

Aaron S Coyner; J. Peter Campbell; Jayashree Kalpathy-Cramer; Praveer Singh; Kemal Sonmez; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2166. doi:

ARVO Annual Meeting Abstract June 2020

Automated Assessment of Stage in Retinopathy of Prematurity using Deep Learning

Jimmy N/A Chen; J. Peter Campbell; Susan Ostmo; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2775. doi:

ARVO Annual Meeting Abstract June 2020

Electronic Health Records in Ophthalmology: Quantitative evaluation of progress note utility for clinical decision-making

Sarah Glass; Adam Rule; Michelle Hribar; Thomas S Hwang; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):5113. doi:

ARVO Annual Meeting Abstract June 2020

Documentation Composition and Efficiency During Scribed and Non-Scribed Ophthalmology Visits

Michelle Hribar; Haley L Dusek; Isaac H Goldstein; Adam Rule; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1587. doi:

ARVO Annual Meeting Abstract June 2020

Evaluation of physician perspectives of artificial intelligence in ophthalmology: a pilot study

Tala Al-Khaled; Nita Valikodath; Emily Cole; Joelle Hallak; J. Peter Campbell; Michael F. Chiang; Robison Vernon Paul Chan

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2023. doi:

ARVO Annual Meeting Abstract June 2020

Analysis of the relationship between retinopathy of prematurity zone, stage, extent and a deep learning-based vascular severity scale

J. Peter Campbell; Robison Vernon Paul Chan; Susan Ostmo; Jamie Anderson; Praveer Singh; Jayashree Kalpathy-Cramer; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):2193. doi:

ARVO Annual Meeting Abstract June 2020

Predicting Late Patients in Pediatric Ophthalmology Outpatient Clinic Using Machine Learning

Wei-Chun Lin; Jimmy N/A Chen; Michelle Hribar; Michael F. Chiang

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):4293. doi:

ARVO Annual Meeting Abstract June 2020

Impacts of Problem-Based Charting on Documentation Time at an Academic Outpatient Ophthalmology Center

Eliesa Ing; Jimmy N/A Chen; Thomas S Hwang; Christina J Flaxel; Michael F. Chiang; Michelle Hribar

Invest. Ophthalmol. Vis. Sci.. 2020; 61(7):1592. doi:

Special Issue February 2020

Applications of Artificial Intelligence to Electronic Health Record Data in Ophthalmology

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Wei-Chun Lin; Jimmy S. Chen; Michael F. Chiang; Michelle R. Hribar
TAGS: artificial intelligence, electronic medical records, ophthalmology
Trans. Vis. Sci. Tech.. 2020; 9(2):13. doi: https://doi.org/10.1167/tvst.9.2.13

Special Issue February 2020

Introduction to Machine Learning, Neural Networks, and Deep Learning

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Rene Y. Choi; Aaron S. Coyner; Jayashree Kalpathy-Cramer; Michael F. Chiang; J. Peter Campbell
TAGS: deep learning, learning, machine learning, datasets
Trans. Vis. Sci. Tech.. 2020; 9(2):14. doi: https://doi.org/10.1167/tvst.9.2.14

Special Issue February 2020

Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach

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Veysi M. Yildiz; Peng Tian; Ilkay Yildiz; James M. Brown; Jayashree Kalpathy-Cramer; Jennifer Dy; Stratis Ioannidis; Deniz Erdogmus; Susan Ostmo; Sang Jin Kim; R. V. Paul Chan; J. Peter Campbell; Michael F. Chiang; for the Imaging and Informatics in Retinopathy of Prematurity (i-ROP) Research Consortium
TAGS: convolutional neural networks, datasets, retinopathy of prematurity, optic disk
Trans. Vis. Sci. Tech.. 2020; 9(2):10. doi: https://doi.org/10.1167/tvst.9.2.10

Includes: Supplemental Content

Special Issue February 2020

Artificial Intelligence in Retinopathy of Prematurity Diagnosis

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Brittni A. Scruggs; R. V. Paul Chan; Jayashree Kalpathy-Cramer; Michael F. Chiang; J. Peter Campbell
TAGS: artificial intelligence, retinopathy of prematurity
Trans. Vis. Sci. Tech.. 2020; 9(2):5. doi: https://doi.org/10.1167/tvst.9.2.5

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Impact of Artificial Intelligence on Medical Education in Ophthalmology

Artificial Intelligence to Reduce Ocular Health Disparities: Moving From Concept to Implementation

Current Challenges and Barriers to Real-World Artificial Intelligence Adoption for the Healthcare System, Provider, and the Patient

Ranibizumab Population Pharmacokinetics and Free VEGF Pharmacodynamics in Preterm Infants With Retinopathy of Prematurity in the RAINBOW Trial

Protecting Data Privacy in the Age of AI-Enabled Ophthalmology

Cost-Utility Analyses of Artificial Intelligence, Telemedicine, and Standard Ophthalmoscopy for Retinopathy of Prematurity Screening

Characterization of response to treatment in infants with retinopathy of prematurity in the ROPE-SOS trial in rural India

Utility of an automated deep learning tool in a low-income country for retinopathy of prematurity

Retinal Fundus Image Generation in Retinopathy of Prematurity Using Autoregressive Generative Models

Automated Assessment of Stage in Retinopathy of Prematurity using Deep Learning

Electronic Health Records in Ophthalmology: Quantitative evaluation of progress note utility for clinical decision-making

Documentation Composition and Efficiency During Scribed and Non-Scribed Ophthalmology Visits

Evaluation of physician perspectives of artificial intelligence in ophthalmology: a pilot study

Analysis of the relationship between retinopathy of prematurity zone, stage, extent and a deep learning-based vascular severity scale

Predicting Late Patients in Pediatric Ophthalmology Outpatient Clinic Using Machine Learning

Impacts of Problem-Based Charting on Documentation Time at an Academic Outpatient Ophthalmology Center

Applications of Artificial Intelligence to Electronic Health Record Data in Ophthalmology

Introduction to Machine Learning, Neural Networks, and Deep Learning

Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach

Artificial Intelligence in Retinopathy of Prematurity Diagnosis

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