Impact and Challenges of Integrating Artificial Intelligence and Telemedicine into Clinical Ophthalmology

Ramessur, Ravi; Raja, Laxmi; Kilduff, Caroline L S; Kang, Swan; Li, Ji-Peng Olivia; Thomas, Peter; Sim, Dawn A

doi:10.1097/apo.0000000000000406

Cited by 20 publications

(19 citation statements)

References 103 publications

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“…A rtificial intelligence (AI) and more specifically, deep learning algorithms, are now capable of recording a level of performance that is, in many cases, comparable to medical practitioners. 1,2 Diabetic retinopathy screening, with its large repository of graded images, has been at the forefront of this technology. The landmark approval of IDx-DR for automated detection of referable diabetic retinopathy by the US Food and Drug Administration in 2018 represented the first of such wide acceptance of an AI system in any field of medicine.…”

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confidence: 99%

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Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening

Yap¹,

Wilkinson

Chen³

et al. 2022

Asia-Pacific Journal of Ophthalmology

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Purpose: Artificial intelligence (AI) technology is poised to revolutionize modern delivery of health care services. We set to evaluate the patient perspective of AI use in diabetic retinal screening. Design: Survey. Methods: Four hundred thirty-eight patients undergoing diabetic retinal screening across New Zealand participated in a survey about their opinion of AI technology in retinal screening. The survey consisted of 13 questions covering topics of awareness, trust, and receptivity toward AI systems. Results: The mean age was 59 years. The majority of participants identified as New Zealand European (50%), followed by Asian (31%), Pacific Islander (10%), and Ma ¯ori (5%). Whilst 73% of participants were aware of AI, only 58% have heard of it being implemented in health care. Overall, 78% of respondents were comfortable with AI use in their care, with 53% saying they would trust an AI-assisted screening program as much as a health professional. Despite having a higher awareness of AI, younger participants had lower trust in AI systems. A higher proportion of Maori and Pacific participants indicated a preference toward human-led screening. The main perceived benefits of AI included faster diagnostic speeds and greater accuracy. Conclusions: There is low awareness of clinical AI applications among our participants. Despite this, most are receptive toward the implementation of AI in diabetic eye screening. Overall, there was a strong preference toward continual involvement of clinicians in the screening process. There are key recommendations to enhance the receptivity of the public toward incorporation of AI into retinal screening programs.

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confidence: 99%

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confidence: 99%

Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening

Yap¹,

Wilkinson

Chen³

et al. 2022

Asia-Pacific Journal of Ophthalmology

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“…Amongst the myriad technological advancements in eye and vision care, one of the most promising is the advent of AI. [ 11 ] With the ever-expanding promise of personalized healthcare, AI may deliver unique results to each patient by utilizing the vast amount of data generated in each clinical encounter [ 65 ].…”

Section: Artificial Intelligencementioning

confidence: 99%

Surfing the COVID-19 Tsunami with Teleophthalmology: the Advent of New Models of Eye Care

Ricur

Reyes

Alfonso

et al. 2023

Curr Ophthalmol Rep

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Purpose of Review In this article, we reviewed the impact resulting from the COVID-19 pandemic on the traditional model of care in ophthalmology. Recent Findings Though virtual eye care has been present for more than 20 years, the COVID-19 pandemic has established a precedent to seriously consider its role in the evolving paradigm of vision and eye care. New hybrid models of care have enhanced or replaced traditional synchronous and asynchronous visits. The increased use of smart phoneography and mobile applications enhanced the remote examination of patients. Use of e-learning became a mainstream tool to continue accessing education and training. Summary Teleophthalmology has demonstrated its value for screening, examining, diagnosing, monitoring treatment, and increasing access to education. However, much of the progress made following the COVID-19 pandemic is at risk of being lost as society pushes to reestablish normalcy. Further studies during the new norm are required to prove a more permanent role for virtual eye care.

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“…Our OCT-based approach, or similar other methodologies, bridge the gap between the present day and the future arrival of artificial intelligence-assisted decision making. [12][13][14] In summary, the use of the term "glaucoma suspect" creates a difficult predicament for both the patient and health care systems and is counterproductive. Patients suffer from the inconvenience, psychological impact and financial implications of a glaucoma suspect diagnosis and health care systems need to cope with provider, technology and cost constraints.…”

Section: How Can This Be Accomplished?mentioning

confidence: 99%

“…An artificial intelligence algorithm, especially with standardization of images,10,11 might also be able improve diagnostic accuracy, but the technology remains nascent. Our OCT-based approach, or similar other methodologies, bridge the gap between the present day and the future arrival of artificial intelligence-assisted decision making 12–14…”

Section: How Can This Be Accomplished?mentioning

confidence: 99%

The Glaucoma Suspect Problem: Ways Forward

Leshno

Liebmann

2022

Asia-Pacific Journal of Ophthalmology

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The diagnosis of glaucoma depends upon indentification of characteristic damage to the optic nerve and retinal fiber layer. In many cases, however, clinicians find it difficult to ascertain whether glaucomatous damage is present or absent. These patients are often labeled as "glaucoma suspects," which creates a subpopulation of individuals without clear-cut disease who nonetheless must remain under surveillance. Most will never go on to develop glaucoma, yet the need for ongoing monitoring burdens clinics and health care systems. In this perspective, we illustrate possible directions and novel approaches that can be used to remedy this situation by integrating current technologies into clinical practice. In particular, we suggest that optical coherence tomography be better utilized to methodologically classify these eyes into glaucomatous and healthy categories.

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Impact and Challenges of Integrating Artificial Intelligence and Telemedicine into Clinical Ophthalmology

Abstract: Supplemental Digital Content is available in the text

Cited by 20 publications

References 103 publications

Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening

Patients Perceptions of Artificial Intelligence in Diabetic Eye Screening

Surfing the COVID-19 Tsunami with Teleophthalmology: the Advent of New Models of Eye Care

The Glaucoma Suspect Problem: Ways Forward

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