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Blinking blepharitis has a lot to answer for…

Never ignore the small things’…someone once said. There is no doubt blepharitis is one of the most common eye conditions encountered daily, but with the typical pressures of a busy outpatient department, the management of more obvious, sight-threatening conditions necessarily...

Redeployment during the COVID-19 pandemic: personal accounts from four ophthalmology trainees

We once believed that the coronavirus would not penetrate the safe confines of the United Kingdom, like so many outbreaks before this. Once the news came that this pandemic descended into our hospitals, the anxieties about redeployment began. Many of...

A new observation point: updating the nomenclature and classification with OCT

The evolution of ophthalmic imaging technologies has been particularly rapid over the last few years. The author provides an update of the current terms for common signs and pathologies observed using optical coherence tomography. My experience as an ophthalmic technician,...

My ophthalmic elective: focusing on myopia in Taiwan

The authors describe their elective experience and delve further into high myopia, an emerging ophthalmic disease that is increasingly recognised in and outside Asia. The medical school elective programme presents an opportunity for students to conduct learning in their chosen...

Dr Glaucomflecken: Stayin’ Alive

Peter Cackett spoke to ophthalmologist and social media sensation Dr Glaucomflecken about his early days in comedy, the role satire can play in impacting medical governance, and where he might take his brand of medical comedy next. It was towards...

Observership in Dar es Salaam

In this report, both authors present their personal experiences of an observership at the Comprehensive Community Based Rehabilitation in Tanzania (CCBRT) Hospital, a large regional teaching hospital located in Dar es Salaam, with a particular focus on resource management, attitudes...

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...