Papers Clinical Knowledge
“Clinical Knowledge” 태그가 달린 논문 220편 · 필터 해제
Clinical Graph-JEPA: Predictive Patient-State Knowledge Graphs for Cognitive Decision Support
Clinical records contain rich evidence about patient state, but converting that evidence into reliable, structured knowledge graphs remains difficult because extraction errors, ontology mismatch, missing relations, and t…
Clinical KnowledgeKnowledge GraphsLarge language models as synthetic clinical experts to inform longitudinal rare-disease modeling
Due to the limited amount of information, modeling longitudinal rare-disease data can benefit from integrating clinical knowledge. Yet, elicitation of expert knowledge and formalization for model fitting is challenging, …
Representation LearningClinical KnowledgeA Neurosymbolic Approach for Explainable Early Diagnosis of Alzheimer's Disease
Identifying reliable Alzheimer's disease (AD) markers typically requires manual, labor-intensive transcription and expert analysis, limiting its scale. We introduce an automated pipeline that extracts qualitative knowled…
Clinical KnowledgeScaFE: Data-Efficient Scar Classification with LLM-Generated Clinical Feature Programs
Classifying pathological scars from clinical photographs requires distinguishing keloids from hypertrophic scars despite limited expert-labeled data and substantial acquisition variation across hospitals. End-to-end imag…
Medical Image ClassificationFeature EngineeringClinical KnowledgeOrthKD: Extracting Generalized Clinical Knowledge from Heterogeneous Teachers for Lightweight Deployment
Deploying diabetic retinopathy (DR) screening models in primary care requires edge-efficient systems that remain accurate, safe, and reliable under domain shift. Multi-teacher knowledge distillation (KD) is a natural com…
Knowledge DistillationClinical KnowledgeEnhancing Explainable Cardiac Diagnosis with Guide-Grounded Multimodal LLMs
The electrocardiogram (ECG) is a cornerstone of cardiac as- sessment, yet clinical deployment of deep learning models remains con- strained by limited interpretability and the hallucination risk of large language models …
Clinical KnowledgeClinical Pathways as Safety Specifications for Physical AI in Hospital Wards
Ensuring safety in Physical AI systems operating in real-world environments is a critical challenge, particularly in hospital wards where vulnerable patients, clinical staff, medical devices, and assistive robots coexist…
Clinical KnowledgeAnomaly DetectionX-FEMR: A Token-level Explainable Approach for Electronic Health Records Foundation Models using Transformer-based Models
Foundation Models for Electronic Health Records (FEMRs) are pretrained on large-scale structured patient data, enabling them to convert longitudinal patient trajectories into generalizable representations for diverse cli…
Clinical KnowledgeEvaluating and Understanding Model Editing for Medical Vision Language Models
Model editing promises a fast, targeted way to correct post-deployment mistakes in medical vision-language models (VLMs) without costly retraining. However, existing multimodal model editing benchmarks focus on general-p…
Clinical KnowledgeDo ECG Foundation Models Transfer to Rare Cardiac Diseases? Evidence from Brugada Syndrome Detection
Background: Foundation models (FMs) trained on large-scale unlabeled physiological data have emerged as a promising paradigm for medical artificial intelligence. Their ability to capture clinically meaningful, transferab…
Clinical KnowledgeMask to Concept: Auto-Promptable SAM3 via Efficient Test-Time Concept Embedding Search for Few-Shot Annotation
Transforming foundation segmentation models from human-prompted tools into auto-promptable annotators is critical for scalable medical data annotation. Current methods commonly depend on external feature matchers or auxi…
Clinical KnowledgeAre LLMs Ready to Assist Physicians? PhysAssistBench for Interactive Doctor-Patient-EHR Assistance
The most plausible near-term role of medical LLMs is to assist rather than replace physicians, yet current evaluations often test isolated capabilities: clinical knowledge, EHR system interaction, or patient communicatio…
Clinical KnowledgeLLM-Based Visual Explanation Evaluation Framework for Assessing the Explainability of Facial Skin Disease Classification Models
This study proposes a domain-specific LLM-based Visual Explanation Evaluation Framework for assessing Grad-CAM explanations in facial skin disease diagnosis models. While previous studies have primarily focused on improv…
Clinical KnowledgePrompt EngineeringData AugmentationOpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Models
High-stakes clinical use of large vision-language models (LVLMs) requires reasoning that is grounded in visual evidence and clinical knowledge, not just correct final answers. We introduce OpenMedReason, a large-scale, o…
Clinical KnowledgeSurgiQ: A Large-Scale Multi-Domain Benchmark for Evaluating Surgical Understanding in Large Language Models
Reliable evaluation of large language models in surgery remains underdeveloped. Broad medical benchmarks test clinical knowledge, while surgery requires procedural reasoning, management trade-offs, negation handling, and…
Clinical KnowledgeHoT-SSM:Higher-order Temporal Knowledge Graph Reasoning with State Space Models for Health Care
Medical knowledge graphs (MKGs) infused with clinical knowledge have been increasingly used to model electronic health records (EHRs) to support interpretable predictions in healthcare domain. However, existing MKG-based…
Representation LearningMortality PredictionClinical KnowledgeKnowledge GraphsCross-Modal Clinical Knowledge Integration for Mammography Report Generation
Breast cancer is a major global health concern, and mammography screening plays a central role in early detection. The large volume of screening examinations creates a substantial workload for radiologists, making accura…
Clinical KnowledgeInternal Representation, Not Clinical Knowledge: Where Apparent LLM Triage Failures Originate
Patient-voiced clinical-triage benchmarks report high under-triage rates for consumer LLMs for constrained multiple-choice output, yet the same cases score differently with free-text. We ask whether output format changes…
Clinical KnowledgeAMNESIA: A Large Scale Medical Unlearning Benchmark Suite with Disease-Informed Analysis
Medical knowledge is continuously evolving. This creates a need to update or selectively forget information encoded in already-trained medical LLMs. Machine unlearning aims to remove the influence of specific training da…
Clinical KnowledgeSafeRx-Agent: A Knowledge-Grounded Multi-Agent Framework for Safe and Explainable Medication Recommendation
Medication recommendation predicts medications for patient visits, but existing methods still face two key challenges. At the model level, traditional drug recommendation methods only predict structured drug codes with l…
Clinical KnowledgeCode Generation