ReviewCurrent opinion in ophthalmology2016
Crowdsourcing: an overview and applications to ophthalmology.
Review in Current opinion in ophthalmology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Crowdsourcing the Citation Screening Process for Systematic Reviews: Validation Study.Journal of medical Internet research · 2019Pooled it
- Assessing Interventions on Crowdsourcing Platforms to Nudge Patients for Engagement Behaviors in Primary Care Settings: Randomized Controlled Trial.Journal of medical Internet research · 2023Trial
- Research on the doctors' win in crowdsourcing competitions: perspectives on service content and competitive environment.BMC medical informatics and decision making · 2023Article
- Leveraging weak supervision to perform named entity recognition in electronic health records progress notes to identify the ophthalmology exam.International journal of medical informatics · 2022Article
- Twitter-based crowdsourcing: What kind of measures can help to end the COVID-19 pandemic faster?Frontiers in medicine · 2022Article
- Video-Based Coaching: Current Status and Role in Surgical Practice (Part 1) From the Society for Surgery of the Alimentary Tract, Health Care Quality and Outcomes Committee.Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract · 2021Review
- Collective intelligence in medical decision-making: a systematic scoping review.BMC medical informatics and decision making · 2019Article
- Collaborative intelligence and gamification for on-line malaria species differentiation.Malaria journal · 2019Article
- Crowdsourced versus expert evaluations of the vesico-urethral anastomosis in the robotic radical prostatectomy: is one superior at discriminating differences in automated performance metrics?Journal of robotic surgery · 2018Article
- Plasmodium species differentiation by non-expert on-line volunteers for remote malaria field diagnosis.Malaria journal · 2018Article
- Translational Devices, Technologies, and Medicines in Clinical Ophthalmology.Journal of ophthalmology · 2017Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
purpose of reviewCrowdsourcing involves the use of the collective intelligence of online communities to produce solutions and outcomes for defined objectives. The use of crowdsourcing is growing in many scientific areas. Crowdsourcing in ophthalmology has been used in basic science and clinical research; however, it also shows promise as a method with wide-ranging applications. This review presents current findings on the use of crowdsourcing in ophthalmology and potential applications in the future. RECENT
findingsCrowdsourcing has been used to distinguish normal retinal images from images with diabetic retinopathy; the collective intelligence of the crowd was able to correctly classify 81% of 230 images (19 unique) for US$1.10/eye in 20 min. Crowdsourcing has also been used to distinguish normal optic discs from abnormal ones with reasonable sensitivity (83-88%), but low specificity (35-43%). Another study used crowdsourcing for quick and reliable manual segmentation of optical coherence tomography images. Outside of ophthalmology, crowdsourcing has been used for text and image interpretation, language translation, and data analysis. SUMMARY: Crowdsourcing has the potential for rapid and economical data processing. Among other applications, it could be used in research settings to provide the 'ground-truth' data, and in the clinical settings to relieve the burden of image processing on experts.
Indexed as
Identifiers
What OpenQuestion holds
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.