Healthcare has long been an exercise in storytelling. Patients bring their narratives to clinicians, who must interpret, analyze, and act upon them. But these narratives are often incomplete—fragments of symptoms shared under the pressure of time constraints, filtered by memory, and limited by the patient’s ability to articulate their experiences. Add to that the key facts and insights that are simply unattainable—by human senses or cognition.

This is where large language models (LLMs) have the potential to evolve care by fostering deeper, iterative dialogues that enhance understanding, improve diagnosis, and build trust.

For decades, the healthcare system has struggled with (at least) two critical challenges: time and information. Clinicians have precious little time, often spending mere minutes with patients while juggling complex histories, diagnoses, and treatment plans. Simultaneously, the sheer volume and complexity of information available can overwhelm even the most experienced providers, making swift interpretation nearly impossible. In this compressed and information-dense environment, the richness of a patient’s story can be lost. LLMs offer a transformative alternative: they listen, probe, and iterate, creating a dynamic dialogue that........

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