ArticleIndian journal of ophthalmology2019
Trash to treasure Retcam.
Article in Indian journal of ophthalmology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Examination under anesthesia: Preferred Practice.Indian journal of ophthalmology · 2023Article
- Universal slit-lamp-mounted mobile adapter with 20 D lens for fundus photography:Indian journal of ophthalmology · 2023Article
- Smartphone co-aided cobalt blue anterior segment with intraocular lens photography.Indian journal of ophthalmology · 2023Article
- Commentary: What the eye sees, Let's make the world see - Smart evolution of teleophthalmology.Indian journal of ophthalmology · 2022Article
- The Gimbalscope - A novel smartphone-assisted retinoscopy technique.Indian journal of ophthalmology · 2022Article
- Development of 3D Printed Smartphone-Based Multi-Purpose Fundus Camera (MultiScope) for Retinopathy of Prematurity.Annals of biomedical engineering · 2021Article
- Commentary: Smartphone-based, wireless, slit-lamp imaging with small footprint - making photodocumentation easy.Indian journal of ophthalmology · 2021Article
- Digital ophthalmoscopy: through a non-specialist lens.Future healthcare journal · 2021Review
- Smartphone-based intraocular lens microscope.Indian journal of ophthalmology · 2020Article
- Commentary: Bringing frugal Indovation to eyes of babies.Indian journal of ophthalmology · 2020Article
- Commentary: Gamifying teleconsultation during COVID-19 lockdown.Indian journal of ophthalmology · 2020Article
- Commentary: Teleophthalmology and electronic medical records: Weighing the pros and cons of unavoidable progress.Indian journal of ophthalmology · 2020Article
- Commentary: The glued intraocular lens smartphone microscope.Indian journal of ophthalmology · 2019Article
- Commentary: Rise of machine learning and artificial intelligence in ophthalmology.Indian journal of ophthalmology · 2019Article
- Commentary: Frugal innovations - Path to eye care for all.Indian journal of ophthalmology · 2019Article
- Commentary: Tsunami of grassroot innovations from makers.Indian journal of ophthalmology · 2019Article
- "Indovation" in ophthalmology - The potential power of frugal innovations.Indian journal of ophthalmology · 2019Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Digital fundus imaging is being used in diagnosis, documentation, and sharing of many retinal diseases and hence forms an essential part of ophthalmology. The use of smartphones for the same has been ever increasing. There is a need for simpler devices to couple the 20D lens and smartphone so as to take fundus photographs which can help in fundus documentation. This article describes a simple inexpensive technique of preparing a smartphone fundus photography device (Trash To Treasure (T3) Retcam) from the used materials in the clinics within minutes. This article will also review the optical principles of the T3 Retcam and describe the step-by-step method to record good-quality retinal image/videos. This inexpensive device is made by recycling and modifying the plastic hand sanitizer bottle in the clinics/hospitals which can be used for documenting, diagnosing, screening, and academic purposes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.