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Deep learning in ophthalmology: The technical and clinical considerations.
Ting, DSW, Peng, L, Varadarajan, AV, Keane, PA, Burlina, PM, Chiang, MF, Schmetterer, L, Pasquale, LR, Bressler, NM, Webster, DR, et al
Progress in retinal and eye research. 2019;:100759
Abstract
The advent of computer graphic processing units, improvement in mathematical models and availability of big data has allowed artificial intelligence (AI) using machine learning (ML) and deep learning (DL) techniques to achieve robust performance for broad applications in social-media, the internet of things, the automotive industry and healthcare. DL systems in particular provide improved capability in image, speech and motion recognition as well as in natural language processing. In medicine, significant progress of AI and DL systems has been demonstrated in image-centric specialties such as radiology, dermatology, pathology and ophthalmology. New studies, including pre-registered prospective clinical trials, have shown DL systems are accurate and effective in detecting diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD), retinopathy of prematurity, refractive error and in identifying cardiovascular risk factors and diseases, from digital fundus photographs. There is also increasing attention on the use of AI and DL systems in identifying disease features, progression and treatment response for retinal diseases such as neovascular AMD and diabetic macular edema using optical coherence tomography (OCT). Additionally, the application of ML to visual fields may be useful in detecting glaucoma progression. There are limited studies that incorporate clinical data including electronic health records, in AL and DL algorithms, and no prospective studies to demonstrate that AI and DL algorithms can predict the development of clinical eye disease. This article describes global eye disease burden, unmet needs and common conditions of public health importance for which AI and DL systems may be applicable. Technical and clinical aspects to build a DL system to address those needs, and the potential challenges for clinical adoption are discussed. AI, ML and DL will likely play a crucial role in clinical ophthalmology practice, with implications for screening, diagnosis and follow up of the major causes of vision impairment in the setting of ageing populations globally.
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Connect between gut microbiome and diseases of the human eye.
Shivaji, S
Journal of biosciences. 2019;(5)
Abstract
Implicating dysbiosis of gut microbiome in digestive tract diseases/diet-related diseases (obesity, inflammatory bowel disease, enterocolitis, diabetes, etc.) may be expected. However, when gut microbiome dysbiosis is implicated in extraintestinal diseases like cancers, muscular dystrophy, mental disorders, vaginosis, etc., it is all the more challenging. An additional challenge would be to ascertain the role of gut microbiome in ocular diseases, which are as remote as the brain. The present review highlights studies that establish the connect between gut microbiome dysbiosis and inflammatory ocular diseases such as uveitis, bacterial keratitis, fungal keratitis, etc.
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3.
Examining the ocular fundus in neurology.
Rodenbeck, SJ, Mackay, DD
Current opinion in neurology. 2019;(1):105-110
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Abstract
PURPOSE OF REVIEW The funduscopic examination can be a technically difficult, and often omitted, portion of the neurologic examination, despite its great potential to influence patient care. RECENT FINDINGS Medical practitioners are often first taught to examine the ocular fundus using a direct ophthalmoscope, however, this skill requires frequent practice. Nonmydriatic tabletop and portable fundus photography and even smartphone-based photography offer alternative and practical means for approaching examination of the ocular fundus. These alternative tools have been shown to be practical in a variety of settings including ambulatory clinics and emergency departments. Decreased retinal microvascular density detected with fundus photography has been linked to accelerated rates of cognitive decline. Research has also found optic disc pallor and retinopathy detected via fundus photography to be more prevalent in patients with recent stroke or transient ischemic attack. SUMMARY Alternative methods of funduscopic examination based on fundus photography have the potential to improve the ease of use, portability, and availability of funduscopy. Recognition of changes in retinal microvasculature has the potential to noninvasively identify patients at the highest risk for cognitive impairment and cerebrovascular disease. However, further research is needed to determine the specific utility of measurements of retinal microvascular changes in clinical care. Innovative funduscopy techniques offer neurologists new approaches to this essential facet of the neurological examination.
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4.
Patient-oriented mobile applications in ophthalmology.
Skrzypecki, J, Stańska, K, Grabska-Liberek, I
Clinical & experimental optometry. 2019;(2):180-183
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Abstract
BACKGROUND Mobile solutions will improve patient care only if they are equally valued by physicians and their patients. Although mobile applications are gaining acceptance among ophthalmologists and optometrists, little is known about their adoption among patients. Therefore, this study was designed to analyse the market for patient-oriented mobile applications in ophthalmology. METHODS Search engines of Google Play and App Store were utilised to find patient-oriented mobile applications. All applications were divided into seven subspecialties; dry eye, strabismus and amblyopia, macular degeneration, cataract, glaucoma, diabetic retinopathy and general ophthalmology. Subsequently, number of downloads, average patient rating, year of release and source of clinical information provided in the application were collected. Furthermore, in order to evaluate whether development of software responds to epidemiological demand, number of applications in each subspecialty was correlated with the prevalence of particular diseases. RESULTS Fifty-six applications that met established criteria were found. The overall number of downloads was estimated at the level of 1.5 million, whereas the weighted average rating for all applications was 4.21/5. The number of applications by subspecialty did not correlate with the prevalence of particular eye disorder. The dry eye was the most frequently downloaded and best rated subspecialty. CONCLUSIONS The overall number of patient-oriented applications in ophthalmology is low. Subspecialties are not equally equipped with patient-oriented mobile solutions. Furthermore, the number of applications or downloads in each subspecialty does not correlate with the number of potential users such as patients with particular eye disorders. Finally, ophthalmologists should encourage software developers to meet future demand for mobile solutions in eye disorders.
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Illicit drugs: Effects on eye.
Dhingra, D, Kaur, S, Ram, J
The Indian journal of medical research. 2019;(3):228-238
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Abstract
There is a myriad of changes that can be produced in the eye by toxic drugs ranging from mild/no symptoms to severe loss of vision from endophthalmitis. The routes of administration include oral ingestion, smoking, nasal inhalation, intravenous injection, topical application or application to other mucosal surfaces. It is important to recognize certain clinical signs and symptoms in the eye produced by these toxins. This article describes in brief some of the ocular effects of commonly abused drugs. For identification of a particular poisoning, in addition to the clinical presentation, pulse, blood pressure, respiration and body temperature, pupillary size, pupillary reaction to light, ocular convergence and nystagmus can be useful indicators of the type of drug the patient is exposed to. Unmasking these features help the clinician in an early and accurate diagnosis of the offending drug as well as timely management.
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Unmet Needs in Ophthalmology: A European Vision Institute-Consensus Roadmap 2019-2025.
Cursiefen, C, Cordeiro, F, Cunha-Vaz, J, Wheeler-Schilling, T, Scholl, HPN, ,
Ophthalmic research. 2019;(3):123-133
Abstract
PURPOSE To define unmet needs in ophthalmology that can realistically be addressed in the next 5 years (2019-2025) and describe potential avenues for research to address these challenges. METHODS Outcomes of a consensus process within the European Vision institute (Brussels) are outlined. Disease areas that are discussed comprise glaucoma, retinal dystrophies, diabetic retinopathy, dry eye disease, corneal diseases, cataract and refractive surgery. RESULTS Unmet needs in the mentioned disease areas are discussed and realistically achievable research projects outlined. CONCLUSIONS Considerable progress can be made in the ophthalmic field and patient-relevant outcomes in the near future.
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Current state and future prospects of artificial intelligence in ophthalmology: a review.
Hogarty, DT, Mackey, DA, Hewitt, AW
Clinical & experimental ophthalmology. 2019;(1):128-139
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Artificial intelligence (AI) has emerged as a major frontier in computer science research. Although AI has broad application across many medical fields, it will have particular utility in ophthalmology and will dramatically change the diagnostic and treatment pathways for many eye conditions such as corneal ectasias, glaucoma, age-related macular degeneration and diabetic retinopathy. However, given that AI has primarily been driven as a computer science, its concepts and terminology are unfamiliar to many medical professionals. Important key terms such as machine learning and deep learning are often misunderstood and incorrectly used interchangeably. This article presents an overview of AI and new developments relevant to ophthalmology.
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The association of other autoimmune diseases in patients with Graves' disease (with or without ophthalmopathy): Review of the literature and report of a large series.
Ferrari, SM, Fallahi, P, Ruffilli, I, Elia, G, Ragusa, F, Benvenga, S, Antonelli, A
Autoimmunity reviews. 2019;(3):287-292
Abstract
Graves' disease (GD) and autoimmune thyroiditis (AT) are the two main clinical presentations of AITD, and their clinical hallmarks are thyrotoxicosis and hypothyroidism, respectively. GD, and AT, can be associated with other organ specific, or systemic autoimmune diseases in the same patient. However discordant results have been reported in the literature about the possible associations. Here, we review the association of GD and other autoimmune syndromes. Furthermore, we report the results of our prospective study that investigated the prevalence of other autoimmune disorders in 3209 GD patients (984 with Graves' ophthalmopathy), with respect to 1069 healthy controls, or 1069 patients with AT, or 1069 with multinodular goiter (matched by age, gender, coming from the same area, with a similar iodine intake). On the whole, 16.7% of GD patients had another associated autoimmune disease; and the most frequently observed were: vitiligo (2.6%), chronic autoimmune gastritis (2.4%), rheumatoid arthritis (1.9%), polymyalgia rheumatica (1.3%), multiple sclerosis (0.3%), celiac disease (1.1%), diabetes (type 1) (0.9%), systemic lupus erythematosus and sarcoidosis (<0.1%), Sjogren disease (0.8%). Moreover, 1.5% patients with GD had three associated autoimmune disorders. Interestingly, patients with Graves' ophthalmopathy (GO) had another autoimmmune disorder more frequently (18.9%), with respect to GD patients without GO (15.6%). However the pattern of the associated autoimmune disorders in GD was not significantly different from that observed in AT patients. In conclusion, we suggest GD patients who are still sick, or who develop new unspecific symptoms (even if during an appropriate treatment of hyperthyroidism) should be appropriately screened for the presence of other autoimmune disorders.
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Promising Artificial Intelligence-Machine Learning-Deep Learning Algorithms in Ophthalmology.
Balyen, L, Peto, T
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.). 2019;(3):264-272
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Abstract
The lifestyle of modern society has changed significantly with the emergence of artificial intelligence (AI), machine learning (ML), and deep learning (DL) technologies in recent years. Artificial intelligence is a multidimensional technology with various components such as advanced algorithms, ML and DL. Together, AI, ML, and DL are expected to provide automated devices to ophthalmologists for early diagnosis and timely treatment of ocular disorders in the near future. In fact, AI, ML, and DL have been used in ophthalmic setting to validate the diagnosis of diseases, read images, perform corneal topographic mapping and intraocular lens calculations. Diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma are the 3 most common causes of irreversible blindness on a global scale. Ophthalmic imaging provides a way to diagnose and objectively detect the progression of a number of pathologies including DR, AMD, glaucoma, and other ophthalmic disorders. There are 2 methods of imaging used as diagnostic methods in ophthalmic practice: fundus digital photography and optical coherence tomography (OCT). Of note, OCT has become the most widely used imaging modality in ophthalmology settings in the developed world. Changes in population demographics and lifestyle, extension of average lifespan, and the changing pattern of chronic diseases such as obesity, diabetes, DR, AMD, and glaucoma create a rising demand for such images. Furthermore, the limitation of availability of retina specialists and trained human graders is a major problem in many countries. Consequently, given the current population growth trends, it is inevitable that analyzing such images is time-consuming, costly, and prone to human error. Therefore, the detection and treatment of DR, AMD, glaucoma, and other ophthalmic disorders through unmanned automated applications system in the near future will be inevitable. We provide an overview of the potential impact of the current AI, ML, and DL methods and their applications on the early detection and treatment of DR, AMD, glaucoma, and other ophthalmic diseases.
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Statins in ophthalmology.
Ooi, KG, Khoo, P, Vaclavik, V, Watson, SL
Survey of ophthalmology. 2019;(3):401-432
Abstract
Statins, 3-hydroxy-3-methyl-gutaryl coenzyme A reductase inhibitors, are a class of lipid-lowering drugs with anti-inflammatory, immunomodulatory, and vascular effects. Statins are increasingly being used in the treatment of a variety of medical conditions. We examine the actions of statins on the eye and its associated ophthalmic disorders. Statins can be synthetic or nonsynthetic, and their differentiating derivations may contribute to their varying cholesterol-lowering and pleiotropic effects. There is conflicting evidence on the ocular therapeutic and adverse effects of the statins. Statins may play a role in reducing the burden of dry eye, corneal ulcer scarring, thyroid-associated orbitopathy, glaucoma, uveitis and other associated ocular inflammatory states, cataract, proliferative vitreoretinopathy, diabetic retinopathy, macular degeneration, and choroidal melanoma. Topical preparations of statins can be formulated, thereby extending the range of ocular diseases that may be amenable to treatment. Statins have a relatively safe side effect profile, but rare and serious adverse reactions have been reported with their usage in ophthalmology, including myopathies and rhabdomyolysis with acute renal failure.