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Updated: Jun 2, 2026

An Assay to Detect Protection of the Retinal Vasculature from Diabetes-Related Death in Mice
04:36

An Assay to Detect Protection of the Retinal Vasculature from Diabetes-Related Death in Mice

Published on: January 12, 2024

[Artificial intelligence in diabetic retinopathy screening].

Éva Volek1,2, Melinda Pénzes1,3, Balázs Szécsényi-Nagy1

  • 11 Semmelweis Egyetem, Egészségügyi Közszolgálati Kar, Egészségügyi Menedzserképző Központ Budapest, Kútvölgyi út 2., 1125 Magyarország.

Orvosi Hetilap
|May 31, 2026
PubMed
Summary

Related Concept Videos

Diabetic Retinopathy01:27

Diabetic Retinopathy

DefinitionDiabetic retinopathy is a microvascular complication of diabetes affecting the retinal blood vessels.Risk FactorsDiabetic retinopathy is present in almost all individuals with type 1 diabetes and more than 60% of those with type 2 diabetes after two decades of disease.The risk increases with poor glycemic control, hypertension, dyslipidemia, smoking, pregnancy, and puberty.Although cataracts and glaucoma are also more frequent in people with diabetes, retinopathy remains the leading...

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Artificial intelligence can improve Hungary's eye screening for diabetic retinopathy, addressing low coverage and workforce shortages. Implementing AI requires funding, regulation, and a hybrid model for a national program to prevent blindness.

Area of Science:

  • Ophthalmology
  • Public Health
  • Artificial Intelligence

Background:

  • Visual impairment and blindness are significant public health issues in Hungary, with high rates in those aged 50+.
  • Approximately 90% of vision loss is preventable or treatable, yet screening coverage remains low.
  • Barriers to effective screening include lack of funding, limited workforce, and absence of a national protocol.

Purpose of the Study:

  • To assess the feasibility of implementing AI-supported ophthalmic screening in Hungary.
  • Focus on diabetic retinopathy screening conditions: professional, organizational, financial, legal, and ethical.
  • Review national data and international best practices for AI in eye care.

Main Methods:

  • Targeted narrative literature review of Hungarian epidemiological, workforce, and cost data.
Keywords:
artificial intelligencediabeteses retinopathiadiabetic retinopathyegészségpolitikafundus screeninghealth policyhuman resourceshumánerőforrásmesterséges intelligenciaszemfenéki szűrés

Related Experiment Videos

Last Updated: Jun 2, 2026

An Assay to Detect Protection of the Retinal Vasculature from Diabetes-Related Death in Mice
04:36

An Assay to Detect Protection of the Retinal Vasculature from Diabetes-Related Death in Mice

Published on: January 12, 2024

  • Analysis of international diabetic retinopathy screening models.
  • Examination of EU regulatory frameworks for AI and medical devices.

    • Main Results:

    • Current Hungarian screening capacity is insufficient for the estimated one million annual diabetic fundus examinations.
    • Screening is not a dedicated service, lacking separate financing and relying on routine outpatient care.
    • International data show AI can enhance diagnostic accuracy and reduce specialist workload in screening.

    Conclusions:

    • AI-supported fundus screening offers potential for improved access, consistency, and efficiency in Hungary.
    • Successful AI implementation necessitates dedicated financing, regulated task-sharing, and adherence to ethical/regulatory standards.
    • A hybrid model, combining validated AI pilots with domestic development, presents a viable path for a national screening program to reduce preventable blindness.