Analysis of the Long-term Visual Outcomes of ForeseeHome Remote Telemonitoring

Mathai, Mariam; Reddy, Shivani; Elman, Michael J.; Garfinkel, Richard A.; Ladd, Byron; Wagner, Alan; Sanborn, George E.; Jacobs, Jennifer; Busquets, Miguel; Chew, Emily Y.

doi:10.1016/j.oret.2022.04.016

Cited by 8 publications

(6 citation statements)

References 29 publications

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“…Distance acuity can be measured by web-based acuity tools such as Myeyes.ai, which pairs to a patient's phone to generate distance-calibrated optotypes [26,27], or Easee.online, which provides home-based visual acuity and refraction capabilities based applications to assess visual acuity [28–30]. There additionally exists an ever-expanding array of smartphone-based applications to assess visual acuity [31 ▪ ,32–36]. However, care should be taken in selecting a visual acuity application, as applications may have variable and inaccurate optotype sizes, and some may not be useful for telemedicine purposes [37].…”

Section: Visual Acuitymentioning

confidence: 99%

Implementation of anterior segment ophthalmic telemedicine

Armstrong,

Liebman,

Ashourizadeh

2024

Current Opinion in Ophthalmology

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Purpose of review The growing push to integrate telemedicine into ophthalmic practices requires physicians to have a thorough understanding of ophthalmic telemedicine's applications, limitations, and recent advances in order to provide well tolerated and appropriate clinical care. This review aims to provide an overview of recent advancements in the use of ophthalmic telemedicine for anterior segment eye examinations. Recent findings Virtual care for anterior segment evaluation relies on appropriate technology, novel workflows, and appropriate clinical case selection. Recent advances, particularly in the wake of the COVID-19 pandemic, have highlighted the utility of home-based assessments for visual acuity, external evaluation, tonometry, and refraction. Additionally, innovative workflows incorporating office-based testing into virtual care, termed ‘hybrid telemedicine’, enable high-quality ophthalmic testing to inform clinical decision-making. Summary Novel digital tools and workflows enable high-quality anterior segment evaluation and management for select ophthalmic concerns. This review highlights the clinical tools and workflows necessary to enable anterior segment telehealth.

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Section: Visual Acuitymentioning

confidence: 99%

Implementation of anterior segment ophthalmic telemedicine

Armstrong,

Liebman,

Ashourizadeh

2024

Current Opinion in Ophthalmology

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“…41 Patients who used these systems for daily self-imaging demonstrated good agreement with expert-based grading, and over a 3-year period, ForeseeHome successfully identified changes in visual acuity and indicated the likelihood that a disease would progress in 2,123 patients. 41,42 These uses highlight AI's critical contribution to improving patient care and AMD research.…”

Section: Use Of Ai-based Ocular Scans In Macular Degenerationmentioning

confidence: 99%

Beyond Vision: Potential Role of AI-enabled Ocular Scans in the Prediction of Aging and Systemic Disorders

Omar,

Abad Ali,

Qabillie

et al. 2024

Siriraj Med J

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In all medical subfields, including ophthalmology, the development of artificial intelligence (AI), particularly cutting-edge deep learning frameworks, has sparked a quiet revolution. The eyes and the rest of the body are anatomically related because of the unique microvascular and neuronal structures they possess. Therefore, ocular image-based AI technology may be a helpful substitute or extra screening method for systemic disorders, particularly in areas with limited resources. This paper provides an overview of existing AI applications for the prediction of systemic diseases from multimodal ocular pictures, including retinal diseases, neurological diseases, anemia, chronic kidney disease, autoimmune diseases, sleep disorders, cardiovascular diseases, and various others. It also covers the process of aging and its predictive biomarkers obtained from AI-based retinal scans. Finally, we also go through these applications existing problems and potential future paths.

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“…The long-term visual outcomes in real-world practice have been analyzed retrospectively. In the 10-year ALOFT study, clinical data of 2123 patients undergoing ForeseeHome monitoring (2010–2020) were examined [25 ▪ ]. Patients demonstrated a high rate of compliance, with an average of 5.2 tests/week.…”

Section: Home Monitoring In Ophthalmologymentioning

confidence: 99%

Artificial intelligence for home monitoring devices

Keenan,

Loewenstein

2023

Current Opinion in Ophthalmology

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Purpose of review Home monitoring in ophthalmology is appropriate for disease stages requiring frequent monitoring or rapid intervention, for example, neovascular age-related macular degeneration (AMD) and glaucoma, where the balance between frequent hospital attendance versus risk of late detection is a constant challenge. Artificial intelligence approaches are well suited to address some challenges of home monitoring. Recent findings Ophthalmic data collected at home have included functional (e.g. perimetry), biometric (e.g. intraocular pressure), and imaging [e.g. optical coherence tomography (OCT)] data. Potential advantages include early detection/intervention, convenience, cost, and visual outcomes. Artificial intelligence can assist with home monitoring workflows by handling large data volumes from frequent testing, compensating for test quality, and extracting useful metrics from complex data. Important use cases include machine learning applied to hyperacuity self-testing for detecting neovascular AMD and deep learning applied to OCT data for quantifying retinal fluid. Summary Home monitoring of health conditions is useful for chronic diseases requiring rapid intervention or frequent data sampling to decrease risk of irreversible vision loss. Artificial intelligence may facilitate accurate, frequent, large-scale home monitoring, if algorithms are integrated safely into workflows. Clinical trials and economic evaluations are important to demonstrate the value of artificial intelligence-based home monitoring, towards improved visual outcomes.

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Analysis of the Long-term Visual Outcomes of ForeseeHome Remote Telemonitoring

Cited by 8 publications

References 29 publications

Implementation of anterior segment ophthalmic telemedicine

Implementation of anterior segment ophthalmic telemedicine

Beyond Vision: Potential Role of AI-enabled Ocular Scans in the Prediction of Aging and Systemic Disorders

Artificial intelligence for home monitoring devices

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