搜索医学 AI 论文与资源

ICLR 2026 Poster accepted paper at ICLR 2026. In precision medicine, quantitative multi-omic features, topological context, and textual biological knowledge play vital roles in identifying disease-critical signaling pathways and targets, guiding the discovery of novel therapeutics and effective treatment strategies. Existing pipelines capture only one or two of these—numerical omics ignore topological context, text-centric LLMs lack quantitative grounded reasoning, and graph-only models underuse rich node semantics and the generalization power of LLMs—thereby limiting mechanistic interpretability. Although Process Reward Models (PRMs) aim to guide reasoning in LLMs, they remain limited by coarse step definitions, unreliable intermediate evaluation, and vulnerability to reward hacking with added computational cost. These gaps motivate jointly integrating quantitative multi-omic signals, topological structure with node annotations, and literature-scale text via LLMs, using subgraph reasoning as the principle bridge linking numeric evidence, topological knowledge and language context.

The Cancer Genome Atlas is a large cancer genomics resource with molecular, clinical, and pathology-related data across many cancer types. It is a foundation dataset for oncology AI, survival prediction, subtype discovery, multimodal cancer modeling, and translational biomarker research.

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.

This Nature Portfolio / npj Cardiovascular Health collection is open for submissions until 2026-06-12. It calls for AI and machine learning work in cardiovascular care, including diagnostic evaluation, CVD risk prediction, cardiac imaging and ECG deep learning, EHR tooling, multi-omics, wearables, remote monitoring, deployment, transparency, ethics, and regulation.

This Frontiers Research Topic calls for work on integrating multi-omics data with clinical information to improve diagnosis, prognosis, and personalized treatment. The page lists a manuscript deadline of 2026-09-14 and is currently accepting articles, making it a relevant journal CFP for clinical translation, multimodal medical AI, and precision medicine.

CCF-Deadlines lists APBC 2026 with papers due 2026-06-15 UTC+0 and conference dates 2026-10-21 to 2026-10-24 in Hsinchu. APBC is directly relevant to medical AI through bioinformatics, computational biology, multi-omics modeling, precision medicine, and AI-assisted biomedical discovery.