搜索医学 AI 论文与资源

ICLR 2026 Poster accepted paper at ICLR 2026. Modeling the temporal dynamics of the human brain remains a core challenge in computational neuroscience and artificial intelligence. Traditional methods often ignore the biological spike characteristics of brain activity and find it difficult to reveal the dynamic dependencies and causal interactions between brain regions, limiting their effectiveness in brain function research and clinical applications. To address this issue, we propose a Spike-based Digital Brain (Spike-DB), a novel fundamental model that introduces the spike computing paradigm into brain time series modeling. Spike-DB encodes fMRI signals as spike trains and learns the temporal driving relationships between anchor and target regions to achieve high-precision prediction of brain activity and reveal underlying causal dependencies and dynamic relationship characteristics. Code/project link: https://github.com/UAIBC-Brain/Spike-DB

ICLR 2026 Poster accepted paper at ICLR 2026. Alzheimer’s Disease (AD) is a progressive neurodegenerative disorder and a leading cause of dementia worldwide. Accurate diagnosis requires integrating diverse patient data modalities. With the rapid advancement of foundation models in neurobiology and medicine, integrating foundation models from various modalities has emerged as a promising yet underexplored direction for multi-modal AD diagnosis. A central challenge is enabling effective interaction among these models without disrupting the robust, modality-specific representations learned from large-scale pretraining. To address this, we propose a novel multi-modal framework for AD diagnosis that enables joint interaction among uni-modal foundation models through modality-anchored interaction.

This Nature Portfolio / npj Gut and Liver collection is open for submissions until 2026-05-12. It welcomes work on risk assessment and early detection of gastrointestinal and liver cancers, including artificial intelligence tools for cancer risk assessment, early-stage detection, novel imaging, tissue acquisition modalities, and health economics for screening.

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 Digital Medicine collection is open for submissions until 2026-07-21. It invites research on AI in sports medicine, including multimodal injury and medical-condition prediction, individualized diagnosis, treatment and rehabilitation, transparent and diverse datasets, open-source explainable AI, and safe AI systems for athlete and exercise health.

This Healthcare special issue focuses on artificial intelligence in public health, healthcare services, and management, including disease surveillance, outbreak prediction, GenAI in diagnostics, imaging and EHRs, patient engagement, and AI ethics and equity. The MDPI flyer lists a manuscript submission deadline of 2026-07-31.

This Diagnostics special issue calls for work on artificial intelligence for health and medicine, in a journal section focused on machine learning and AI in diagnostics. It is relevant to medical imaging, diagnostic pathology and radiology, digital health, rehabilitation, cybersecurity, patient safety, and clinical AI quality. The page lists a manuscript submission deadline of 2026-12-31.

The INFORMS Journal on Data Science CFP focuses on artificial intelligence and data science for healthcare. It is relevant to medical AI work on clinical prediction, decision support, operations, fairness, reliability, and deployment of data-driven healthcare systems. The CFP page lists a 2026 special issue call and submission timeline.

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.

This Taylor & Francis / Risk Management and Healthcare Policy article collection focuses on artificial intelligence in healthcare risk management, including AI applications for early disease detection, personalized treatment optimization, real-time risk prediction, patient safety, and health-system risk management. The CFP listing gives a 2026-05-31 submission deadline.

CCF-Deadlines lists PRICAI 2026 with papers due 2026-06-13 UTC-12 and conference dates 2026-11-17 to 2026-11-20 in Guangzhou. PRICAI is a general AI venue relevant to medical AI methods, clinical decision support, medical agents, and trustworthy healthcare AI.

FutureLearn's Artificial Intelligence for Healthcare course covers AI concepts, tools, ethics, diagnostics, patient care, operational efficiency, personalized medicine, and robotic surgery. The page lists 8 weeks at 2 hours per week and introductory level.

Stanford AIMI Grand Rounds seminar series on artificial intelligence in medicine and imaging.

Harvard Medical School HMX Pro online course on applying artificial intelligence in medicine.

Stanford Center for Artificial Intelligence in Medicine and Imaging course page covering AIMI short courses and programs.