Cian O Hughes

Abstract Real-world clinical practice is inherently multimodal, relying on the synthesis of patient history with visual information such as medical imagery and clinical documents. Although large language models (LLMs) have shown promise in diagnostic dialogue, their evaluation has been largely restricted to text-only interactions, failing to capture the complexity of modern remote care delivery.

More than new cancer cases are diagnosed globally each year, and radiotherapy is one of the most common cancer treatments—used to treat over half of cancers in the United States. But planning for a course of radiotherapy treatment is often a time-consuming and manual process for clinicians.

Abstract Progression to exudative ‘wet’ age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD in the second eye.