Using Imaging to Understand the Causes and Sequelae of Hypotony

Poojitha Balakrishnan, MD, MPH, PhD

Eyetube

Poojitha Balakrishnan, MD, MPH, PhD, recaps her article “Using Imaging to Understand the Causes and Sequelae of Hypotony,” written with Jithin Yohannan, MD, MPH, and featured in the March/April issue of Glaucoma Today. Hypotony is a significant complication of glaucoma surgery, and identifying its causes and sequelae can be a challenge with slit-lamp examinations and indirect ophthalmoscopy alone. Dr. Balakrishnan discusses the value of ocular imaging modalities such as OCT and ultrasound as additional tools for diagnosis and management.

Personalizing Myopia Management

Consider these nonvisual factors when determining which intervention to prescribe to children.

Cynthia Noorani, OD, MPH, FAAO

Modern Optometry

AI Chatbots in the Retina Clinic

Large language models are not coming for your job. But they may redefine what your job looks like.

Fares Antaki, MDCM

Retina Today

KEY TAKEAWAYS Large language models have embedded ophthalmic knowledge that is improving rapidly with each model generation. Practical applications for retina specialists span two categories: workflow improvement (electronic health record documentation, report generation) and clinical assistance (triage, decision support). Vibe coding allows retina specialists without programming experience to build custom clinical tools using large language models. AI has been in ophthalmology for years, and most retina specialists are familiar with AI as it relates to image analysis. Algorithms that detect diabetic retinopathy (DR) from fundus photographs or segment fluid on OCT have received the most attention and, in the case of autonomous DR screening, regulatory clearance.1,2 However, a second wave of AI is reaching the clinic, and this version can read, write, and reason with text. These large language models (LLMs) power the chatbots that are quietly changing how physicians work.3 WHAT ARE LARGE LANGUAGE MODELS? LLMs are a class of AI designed to understand and generate human language. The technology behind products such as ChatGPT (OpenAI), Gemini (Google), and Claude (Anthropic) is conceptually straightforward. During training, a model is shown massive amounts of text and learns to predict the next word in a sequence.4 Consider the phrase attributed to Heraclitus: “The only constant in life is change.”5 A model in training would see “The only constant in life is…” and learn to predict “change.” This process is repeated billions of times across the entirety of the internet, books, and encyclopedias. The result is a system with a broad representation of human knowledge.