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Large language models in ophthalmology

Traditional artificial intelligence (AI) models typically require large amounts of labelled data for training. For example, to develop a model capable of detecting macular pathologies on optical coherence tomography scans, thousands of scans would need to be manually labelled by...

High quality retinal image grading and management service by the NetwORC UK

In 2004 a network of three ophthalmic reading centres in Belfast, London and Liverpool (known as NetwORC UK) was established to form the largest reading centre in Europe for the purpose of providing high quality grading of ophthalmic images for...

An introduction to research governance

Research is the process of acquiring new generalisable knowledge and should be fully integrated into health care work. There is a growing drive to encourage and further develop evidence-based practice in ophthalmology so that staff and patients benefit from improved...

Unconscious bias (part 2)

Does unconscious bias exist, and does training help to reduce discriminatory behaviour? Clare Inkster questions her role as a trainer. I read Gwyn Williams’ Learning Curve article on this topic a few months ago with interest, and as someone who...

Retinoblastoma – the challenges of a rare cancer and the role of international partnerships

Introduction: the global challenge The global burden of retinoblastoma (Rb) is one in 15,000-18,000 live births, which equates to 8000 new cases worldwide each year. The global disparities in Rb outcome represent a paradigm of health inequality worldwide [1]. In...

University of Gloucestershire launches first of its kind ophthalmic imaging degree

Ophthalmic science is a dynamic and constantly evolving profession, with ophthalmic imagers / technicians fundamental to the smooth and efficient running of ophthalmology departments. Traditionally, as the role has developed, ophthalmic imagers have come from a variety of backgrounds, finding...