Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Issues And Trends In Healthcare Delivery System

Issues And Trends In Healthcare Delivery System

The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Correction: Enhancing fault detection in new energy vehicles via novel ensemble approach.

Scientific reports·2026

Same author

Gene therapy for wet AMD: a paradigm shift in the standard of care.

Expert opinion on emerging drugs·2026

Same author

Explainable VGG16 transfer learning with SHAP and grad-CAM for wax moth pest and infestation detection in honeybee apiaries using imaging data.

Scientific reports·2026

Same author

XceptRf-Net: A Novel Deep Learning and Machine Learning Approach for Pneumonia Diagnosis.

Current medical imaging·2026

Same author

Enhancing fault detection in new energy vehicles via novel ensemble approach.

Scientific reports·2026

Same author

A novel hybrid approach for multi stage kidney cancer diagnosis using RCC ProbNet.

Scientific reports·2025

Search research articles

Related Experiment Video

Updated: Jul 2, 2025

$Subjective Refraction Test Using a Smartphone for Vision Screening$

Subjective Refraction Test Using a Smartphone for Vision Screening

Published on: October 18, 2024

Improving Access to Eye Care Through Community Health Screenings Using Artificial Intelligence.

Bhakti Panchal¹, Samuel Asanad¹, Rana Malek²

¹Department of Ophthalmology and Visual Sciences, University of Maryland, Baltimore, Maryland, USA.

Ophthalmic Epidemiology

|February 21, 2024

Summary

Artificial intelligence (AI)-based vision screening was implemented at a community health fair. This innovative approach shows promise for improving access to essential eyecare services for underserved populations.

Keywords:

Eye care artificial intelligence community health screenings diabetic retinopathy screening vision screening

More Related Videos

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment

Published on: March 24, 2020

Related Experiment Videos

Last Updated: Jul 2, 2025

$Subjective Refraction Test Using a Smartphone for Vision Screening$

Subjective Refraction Test Using a Smartphone for Vision Screening

Published on: October 18, 2024

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Author Spotlight: An Automated Method for Assessing Visual Acuity in Infants and Toddlers Using an Eye-Tracking System

Published on: March 17, 2023

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment

Using an Automated Hirschberg Test App to Evaluate Ocular Alignment

Published on: March 24, 2020

Area of Science:

Ophthalmology
Public Health
Artificial Intelligence

Background:

Community health fairs offer a unique venue for health screenings.
Limited access to regular eyecare is a significant public health concern.
The integration of artificial intelligence (AI) in healthcare is rapidly expanding.

Purpose of the Study:

To explore the implementation of AI-based vision screening in a community health fair.
To assess the feasibility and impact of AI in improving access to eyecare.
To identify barriers to eyecare and evaluate eye health literacy within the community.

Main Methods:

A prospective cohort study was conducted during a community health fair.
AI-based non-mydriatic fundus cameras were utilized for vision screening.
Questionnaires were administered to gather data on eyecare barriers and health literacy.

Main Results:

53 individuals underwent AI-powered vision screening.
Approximately 88% of participants scheduled follow-up appointments, with a 62% attendance rate.
Lack of health insurance and transportation were the primary reported barriers to eyecare.

Conclusions:

AI-based vision screening can be effectively integrated into community health fair settings.
This approach has the potential to significantly enhance access to crucial eyecare services.
Addressing socioeconomic factors like insurance and transportation is vital for improving eye health outcomes.