Background Large language models (LLMs) are increasingly used to generate medical assessment items, but their reliability for disease-specific question writing remains uncertain. We benchmarked seven LLMs for epilepsy single-best-answer multiple-choice question generation under a standardized blueprint, focusing on str...
Chao Li, Wei-Fang Wang, Chen-Chen Li et al.· Frontiers in Medicine· 0 citations
This study presents ECloudGen, which uses latent diffusion to generate electron clouds from protein pockets and decodes them into molecules, and adopts two-stage training, which expands the chemical space accessible to generative drug design.
NACraft, a training-free and programmatic framework for all-atom nucleic-acid aptamer design based on backpropagation through structure-model feedback, is presented, demonstrating the effectiveness and versatility of NACraft and extending structure-model hallucination toward programmatic nucleic-acid aptamer design.
