Early-career researchers in clinical fields face a major bottleneck. Generating truly novel and high-quality research hypotheses takes significant time and cognitive effort. This leaves less bandwidth for actually executing studies, running experiments, and translating ideas into published work.

This commentary explores whether large language models can meaningfully support junior researchers by helping them generate fresh clinical research ideas at scale.