搜索医学 AI 论文与资源

ICLR 2026 Poster accepted paper at ICLR 2026. Accurate detection of clinically meaningful events in healthcare time-series data is crucial for reliable downstream analysis and decision support. However, most existing methods struggle to jointly localize event boundaries and classify event types; even detection transformer (DETR)-based approaches show limited performance when confronted with extremely sparse events typical of clinical recordings. To address these challenges, we propose a coarse-to-fine detection framework combining a global context explorer, a local detail inspector, and an adaptive gating module (AGM) that fuses multiple label perspectives. The AGM uses transformed labels—encoding event presence and temporal position—to improve learning on sparse events.

ICLR 2026 Poster accepted paper at ICLR 2026. Clinical decision-making is a dynamic, interactive, and cyclic process where doctors have to repeatedly decide on which clinical action to perform and consider newly uncovered information for diagnosis and treatment. Large Language Models (LLMs) have the potential to support clinicians in this process, however, most applications of LLMs in clinical decision support suffer from one of two limitations: Either they assume the unrealistic scenario of immediate availability of all patient information and do not model the interactive and iterative investigation process, or they restrict themselves to the limited "out-of-the-box" capabilities of large pre-trained models without performing task-specific training. In contrast to this, we propose to model clinical decision-making for diagnosis with a hypothesis-driven uncertainty-aware language agent, LA-CDM, that converges towards a diagnosis via repeatedly requesting and interpreting relevant tests. Using a hybrid training paradigm combining supervised and reinforcement learning, we train LA-CDM with three objectives targeting critical aspects of clinical decision-making: accurate hypothesis generation, hypothesis uncertainty estimation, and efficient decision-making. Code/project link: https://github.com/dharouni/LA-CDM

This Nature Portfolio / Scientific Reports collection is open for submissions until 2026-06-23. It focuses on AI for clinical decision-making, including diagnostic, prognostic, and therapeutic decision support, EHRs, medical imaging, genomics, real-time patient data, clinical notes, multimodal learning, privacy-preserving AI, interpretability, and validation.

This Nature Portfolio / npj Digital Medicine collection is open for submissions until 2026-05-06. It calls for physics-informed machine learning for personalized disease prediction, prevention, and management, including digital twins, physics-informed generative AI, biomedical time-series, signals, images, interpretability, and clinical decision support.

This Nature Portfolio / npj Digital Medicine collection is open for submissions until 2026-07-12. It calls for work on agentic AI in care delivery, including real-time evidence-based decision support, virtual and remote patient care, multimodal and longitudinal clinical data, EHRs, medical imaging, genomics, resource-limited deployment, ethics, regulation, quality, and patient safety.

This Technologies special issue calls for work on AI-enabled smart healthcare systems. It is relevant to medical AI submissions on intelligent monitoring, anomaly detection, assistive technologies, smart sensing, clinical decision support, and AI-assisted healthcare workflows. The page lists a manuscript submission deadline of 2026-08-30.

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.

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.

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.

CCF-Deadlines lists ICTAI 2026 with papers due 2026-06-30 AoE and conference dates 2026-11-02 to 2026-11-04 in Boca Raton. ICTAI is relevant to medical AI tools, clinical decision-support systems, medical LLM agents, and deployable AI techniques for healthcare workflows.

IEEE BIBM 2026 covers bioinformatics, biomedicine, and health informatics, including machine learning and AI, biomedical image analysis, biomedical signal analysis, clinical decision support, EHR standards, healthcare knowledge representation, NLP and text mining, and precision medicine. The official CFP lists electronic submission of full papers due 2026-07-05, notification on 2026-09-25, camera-ready on 2026-10-25, and the conference on 2026-12-01 to 2026-12-04 in Dallas.