搜索医学 AI 论文与资源

ICLR 2026 Poster accepted paper at ICLR 2026. Fusing histopathology images and genomics data with deep learning has significantly advanced precision oncology. However, genomics data is often missing due to its high acquisition cost and complexity in real-world clinical scenarios. Existing solutions aim to reconstruct genomics data from histopathology images. Nevertheless, these methods typically relied only on individual case and overlooked the potential relationships among cases. Additionally, they failed to take advantage of the authentic genomics data of diagnostically related cases that are accessible from training for inference. In this work, we propose a novel Multi-modal Structural Representation Learning (MSRL) framework for data-efficient precision oncology. Code/project link: https://github.com/WkEEn/MSRL

This Nature Portfolio / npj Genomic Medicine collection is open for submissions until 2026-06-23. It covers AI-powered genomic medicine, including variant prioritization, pathway inference, AI prediction from clinical assays such as histology, radiology and EHRs, multi-omics, precision oncology, rare diseases, population health, explainability, bias, and clinical implementation.