搜索医学 AI 论文与资源

ICLR 2026 Poster accepted paper at ICLR 2026. The goal of personalized medicine is to discover a treatment regimen that optimizes a patient's clinical outcome based on their personal genetic and environmental factors. However, candidate treatments cannot be arbitrarily administered to the patient to assess their efficacy; we often instead have access to an *in silico* surrogate model that approximates the true fitness of a proposed treatment. Unfortunately, such surrogate models have been shown to fail to generalize to previously unseen patient-treatment combinations. We hypothesize that domain-specific prior knowledge—such as medical textbooks and biomedical knowledge graphs—can provide a meaningful alternative signal of the fitness of proposed treatments.

This Nature Portfolio / npj Digital Medicine collection is open for submissions until 2027-04-30. It invites work at the intersection of computational drug repurposing, multimodal biomedical data, and AI, including omics, EHRs, real-world evidence, imaging, digital phenotyping, LLMs, graph neural networks, multimodal transformers, knowledge graphs, generative AI, causal inference, explainability, and clinical translation.

CCF-Deadlines lists ISWC 2026 with full papers due 2026-05-07 AoE, after an abstract deadline on 2026-05-02, and conference dates 2026-10-25 to 2026-10-29 in Bari. ISWC is relevant to medical AI through biomedical knowledge graphs, clinical ontologies, semantic data integration, and explainable clinical decision support.