-
1.
Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective.
Li, JO, Liu, H, Ting, DSJ, Jeon, S, Chan, RVP, Kim, JE, Sim, DA, Thomas, PBM, Lin, H, Chen, Y, et al
Progress in retinal and eye research. 2021;:100900
-
-
Free full text
-
Abstract
The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a "new normal", the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions.
-
2.
COVID-19 Launches Retinal Telemedicine into the Next Frontier.
Raparia, E, Husain, D
Seminars in ophthalmology. 2021;(4):258-263
Abstract
INTRODUCTION Telemedicine in ophthalmology, and specifically in retinal diseases, has made significant advancements in recent years. The COVID-19 pandemic has launched telehealth into a new era by creating demand from patients and physicians alike, while breaking down previous insurance, reimbursement, access and educational barriers. METHODS This paper reviews mulitple studies demonstrating the use of telemedicine in managing various retinal conditions before and during the COVID-19 pandemic. CONCLUSION Moving forward, promising new devices and models of care ensure that tele-retinal care will continue to expand and become a vital part of how we screen, diagnose and monitor retinal diseases.
-
3.
Artificial intelligence for anterior segment diseases: Emerging applications in ophthalmology.
Ting, DSJ, Foo, VH, Yang, LWY, Sia, JT, Ang, M, Lin, H, Chodosh, J, Mehta, JS, Ting, DSW
The British journal of ophthalmology. 2021;(2):158-168
Abstract
With the advancement of computational power, refinement of learning algorithms and architectures, and availability of big data, artificial intelligence (AI) technology, particularly with machine learning and deep learning, is paving the way for 'intelligent' healthcare systems. AI-related research in ophthalmology previously focused on the screening and diagnosis of posterior segment diseases, particularly diabetic retinopathy, age-related macular degeneration and glaucoma. There is now emerging evidence demonstrating the application of AI to the diagnosis and management of a variety of anterior segment conditions. In this review, we provide an overview of AI applications to the anterior segment addressing keratoconus, infectious keratitis, refractive surgery, corneal transplant, adult and paediatric cataracts, angle-closure glaucoma and iris tumour, and highlight important clinical considerations for adoption of AI technologies, potential integration with telemedicine and future directions.
-
4.
Impact of teleophthalmology during COVID-19 lockdown in a tertiary care center in South India.
Ravindran, M, Segi, A, Mohideen, S, Allapitchai, F, Rengappa, R
Indian journal of ophthalmology. 2021;(3):714-718
-
-
Free full text
-
Abstract
PURPOSE The aim of this study was to describe the experience of teleconsultations addressed at our hospital in India during the ongoing coronavirus (COVID-19) lockdown. METHODS This cross-sectional hospital-based study included 977 teleconsultations presenting between April 1st and May 31, 2020. A two-level protocol was implemented to triage the calls. RESULTS Overall, 977 teleconsultation were addressed. Of the 621 teleconsultation addressed the most common queries were related to redness/pain/ watering/blurred vision/itching/irritation (52.49%), followed by queries related to medications (28.01%), appointments (18.84%) & 0.64% cited an emergency need to visit the hospital due to sudden loss of vision. The majority of the queries were directed to the department of cornea (58.93%) followed by retina (16.26%), cataract (13.04%), glaucoma (10.14%) & pediatric ophthalmology (1.61%). The most common advice given to the patient was related to medications (47.66%) followed by appointment-related queries (31.72%) & fixing of surgical appointment (20.61%). Among the 356 preterm babies that were screened, 57 (16.01%) were diagnosed with retinopathy of prematurity (ROP). Of them 3 required laser and 3 were given injection. CONCLUSION Teleconsultation is here to stay beyond the pandemic. WhatsApp was the preferred modality of communication for us. Teleophthalmology has given us insights to use this evolving technology to reach out to the population at large to provide eye care services. We believe that this mode of teleophthalmology has helped us in providing feasible eye care to the patients.
-
5.
Teleophthalmology for the elderly population: A review of the literature.
Fatehi, F, Jahedi, F, Tay-Kearney, ML, Kanagasingam, Y
International journal of medical informatics. 2020;:104089
Abstract
BACKGROUND Ophthalmology is one of the most requested medical speciality services in the elderly population. Although numerous studies have shown the potentials of telemedicine for the provision of ophthalmology services, the extent of its usability in older adults and the aged population is not clear. The aim of this study was to investigate the characteristics and usability features of teleophthalmology for the elderly population. METHOD We searched PubMed, Embase, Scopus and CINAHL for relevant studies since 2008. Forty-five papers met the eligibility criteria and included in this review. We used a multifaceted model to extract the data and analyze findings by cross-tabulation. RESULTS The majority of the reviewed papers included participants of 65 years of age or older. Most of the studies were conducted in the USA (38 %). Diabetic retinopathy, glaucoma, age-related macular degeneration and cataract were the most researched eye diseases, and among the imaging technologies, retinal photography had been used the most (72 %). The studies showed teleophthalmology can improve access to specialty care, reduce the number of unnecessary visits, alleviate overloads on treatment centers, and provide more comprehensive exams. It also made services cost-saving for stakeholders and cost-effective in rural areas. However, teleophthalmology was not cost-effective for patients above 80 and low-density population areas. CONCLUSION Evidence is lacking for the usability and effectiveness of teleophthalmology for the elderly population. The findings suggest that primary care providers in collaboration with ophthalmologists could provide more effective eye care to elderly population. Appropriate training is also necessary for primary care doctors to manage and refer older patients in a timely manner. Diagnostic value and cost-effective imaging modalities which are the core of the teleophthalmology, can be enhanced by image processing techniques and artificial intelligence.
-
6.
Advances in Telemedicine in Ophthalmology.
Parikh, D, Armstrong, G, Liou, V, Husain, D
Seminars in ophthalmology. 2020;(4):210-215
Abstract
Telemedicine is the provision of healthcare-related services from a distance and is poised to move healthcare from the physician's office back into the patient's home. The field of ophthalmology is often at the forefront of technological advances in medicine including telemedicine and the use of artificial intelligence. Multiple studies have demonstrated the reliability of tele-ophthalmology for use in screening and diagnostics and have demonstrated benefits to patients, physicians, as well as payors. There remain obstacles to widespread implementation, but recent legislation and regulation passed due to the devastating COVID-19 pandemic have helped to reduce some of these barriers. This review describes the current status of tele-ophthalmology in the United States including benefits, hurdles, current programs, technology, and developments in artificial intelligence. With ongoing advances patients may benefit from improved detection and earlier treatment of eye diseases, resulting in better care and improved visual outcomes.
-
7.
Artificial Intelligence and Ophthalmology.
Keskinbora, K, Güven, F
Turkish journal of ophthalmology. 2020;(1):37-43
Abstract
Artificial intelligence is advancing rapidly and making its way into all areas of our lives. This review discusses developments and potential practices regarding the use of artificial intelligence in the field of ophthalmology, and the related topic of medical ethics. Various artificial intelligence applications related to the diagnosis of eye diseases were researched in books, journals, search engines, print and social media. Resources were cross-checked to verify the information. Artificial intelligence algorithms, some of which were approved by the US Food and Drug Administration, have been adopted in the field of ophthalmology, especially in diagnostic studies. Studies are being conducted that prove that artificial intelligence algorithms can be used in the field of ophthalmology, especially in diabetic retinopathy, age-related macular degeneration, and retinopathy of prematurity. Some of these algorithms have come to the approval stage. The current point in artificial intelligence studies shows that this technology has advanced considerably and shows promise for future work. It is believed that artificial intelligence applications will be effective in identifying patients with preventable vision loss and directing them to physicians, especially in developing countries where there are fewer trained professionals and physicians are difficult to reach. When we consider the possibility that some future artificial intelligence systems may be candidates for moral/ethical status, certain ethical issues arise. Questions about moral/ethical status are important in some areas of applied ethics. Although it is accepted that current intelligence systems do not have moral/ethical status, it has yet to be determined what the exact the characteristics that confer moral/ethical status are or will be.
-
8.
Metabolomic analysis in ophthalmology.
Nazifova-Tasinova, N, Radeva, M, Galunska, B, Grupcheva, C
Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia. 2020;(3):236-246
Abstract
Modern science takes into account phenotype complexity and establishes approaches to track changes on every possible level. Many "omics" studies have been developed over the last decade. Metabolomic analysis enables dynamic measurement of the metabolic response of a living system to a variety of stimuli or genetic modifications. Important targets of metabolomics is biomarker development and translation to the clinic for personalized diagnosis and a greater understanding of disease pathogenesis. The current review highlights the major aspects of metabolomic analysis and its applications for the identification of relevant predictive, diagnostic and prognostic biomarkers for some ocular diseases including dry eye, keratoconus, retinal diseases, macular degeneration, and glaucoma. To date, possible biomarker candidates for dry eye disease are lipid metabolites and androgens, for keratoconus cytokeratins, urea, citrate cycle, and oxidative stress metabolites. Palmitoylcarnitine, sphingolipids, vitamin D related metabolites, and steroid precursors may be used for distinguishing glaucoma patients from healthy controls. Dysregulation of amino acid and carnitine metabolism is critical in the development and progression of diabetic retinopathy. Further work is needed to discover and validate metabolic biomarkers as a powerful tool for understanding the molecular mechanisms of ocular diseases, to provide knowledge on their etiology and pathophysiology and opportunities for personalized clinical intervention at an early stage.
-
9.
Smartphone use in ophthalmology: What is their place in clinical practice?
Hogarty, DT, Hogarty, JP, Hewitt, AW
Survey of ophthalmology. 2020;(2):250-262
Abstract
Smartphones are an increasingly common and rapidly developing tool in clinical practice. Numerous applications or "apps" are available for use on smartphones that aim to help clinicians perform a variety of tasks at the point of care. A large number of ophthalmology-related medical apps that can perform a variety of clinically relevant functions are now available in virtual stores such as the Google Play™ Store or the Apple App Store®. On the ophthalmic front, these include measures of visual acuity, tools to assist in the assessment and treatment of conditions such as amblyopia and glaucoma, as well as add-on devices that allow visualization and photography of the anterior and posterior segments of the eye. Despite the large number of available programs, the evidence supporting their use is unclear, with issues concerning professional input in development, regulation, validation, and security of information. We present the various uses of smartphones in ophthalmology and summarize the current literature.
-
10.
Ophthalmic diagnosis using deep learning with fundus images - A critical review.
Sengupta, S, Singh, A, Leopold, HA, Gulati, T, Lakshminarayanan, V
Artificial intelligence in medicine. 2020;:101758
Abstract
An overview of the applications of deep learning for ophthalmic diagnosis using retinal fundus images is presented. We describe various retinal image datasets that can be used for deep learning purposes. Applications of deep learning for segmentation of optic disk, optic cup, blood vessels as well as detection of lesions are reviewed. Recent deep learning models for classification of diseases such as age-related macular degeneration, glaucoma, and diabetic retinopathy are also discussed. Important critical insights and future research directions are given.