Medical AI
Papers in Medical AI
50 papers
- Med-MMFL: A Multimodal Federated Learning Benchmark in Healthcare
Med-MMFL provides the first comprehensive multimodal federated learning benchmark to enhance medical AI research while maintaining data privacy.
Medical AIViability: 5.0 - Self-MedRAG: a Self-Reflective Hybrid Retrieval-Augmented Generation Framework for Reliable Medical Question Answering
Self-MedRAG enhances medical question answering reliability by integrating hybrid retrieval and iterative self-reflection.
Medical AIViability: 8.0 - ART: Action-based Reasoning Task Benchmarking for Medical AI Agents
Develop an advanced benchmark for evaluating and improving medical AI agents' clinical reasoning using real-world EHR data.
Medical AIViability: 7.0 - SRU-Pix2Pix: A Fusion-Driven Generator Network for Medical Image Translation with Few-Shot Learning
Enhanced Pix2Pix framework optimizes MRI imaging with few-shot learning for faster, cost-effective medical diagnostics.
Medical AIViability: 7.0 - DSA-SRGS: Super-Resolution Gaussian Splatting for Dynamic Sparse-View DSA Reconstruction
DSA-SRGS enhances resolution in dynamic 4D angiography models, improving cerebrovascular diagnosis precision.
Medical AIViability: 8.0 - A Unified XAI-LLM Approach for EndotrachealSuctioning Activity Recognition
Develop an AI-powered tool to improve nurse training in endotracheal suctioning through video-based activity recognition using explainable AI.
Medical AIViability: 8.0 - Empowering Medical Equipment Sustainability in Low-Resource Settings: An AI-Powered Diagnostic and Support Platform for Biomedical Technicians
AI-powered platform aiding biomedical technicians in LMICs with real-time medical equipment diagnostics and repair.
Medical AIViability: 7.0 - Zero-shot System for Automatic Body Region Detection for Volumetric CT and MR Images
Zero-shot body region detection system for CT and MR imaging enhances medical analysis by eliminating reliance on DICOM metadata.
Medical AIViability: 7.0 - Cite-While-You-Generate: Training-Free Evidence Attribution for Multimodal Clinical Summarization
Attention-guided attribution for multimodal clinical summarization improves transparency and accuracy without retraining models.
Medical AIViability: 6.0 - AgentsEval: Clinically Faithful Evaluation of Medical Imaging Reports via Multi-Agent Reasoning
AgentsEval enhances the clinical reliability of AI-generated medical imaging reports by using multi-agent stream reasoning for evaluation.
Medical AIViability: 5.0 - Evaluating Large Vision-language Models for Surgical Tool Detection
Develop AI models for detecting surgical tools using large vision-language models to enhance surgical guidance.
Medical AIViability: 5.0 - LLM is Not All You Need: A Systematic Evaluation of ML vs. Foundation Models for text and image based Medical Classification
A benchmark study evaluating the performance of classical ML versus transformer-based models in medical classification tasks.
Medical AIViability: 5.0 - Atlas 2 -- Foundation models for clinical deployment
Atlas 2 offers state-of-the-art pathology vision models designed for clinical deployment with enhanced performance and efficiency.
Medical AIViability: 8.0 - Health-SCORE: Towards Scalable Rubrics for Improving Health-LLMs
Health-SCORE makes rubric development for evaluating Health-LLMs more scalable and cost-effective.
Medical AIViability: 3.0 - A Multi-scale Linear-time Encoder for Whole-Slide Image Analysis
MARBLE offers a scalable, efficient tool for multi-scale whole-slide image analysis with significant accuracy improvements.
Medical AIViability: 8.0 - User-Adaptive Meta-Learning for Cold-Start Medication Recommendation with Uncertainty Filtering
MetaDrug is a meta-learning framework for personalized medication recommendation addressing the cold-start problem in new patients using EHR data.
Medical AIViability: 7.0 - Temporal Context and Architecture: A Benchmark for Naturalistic EEG Decoding
Develop a high-accuracy EEG decoding tool for neurological applications leveraging efficient model architectures.
Medical AIViability: 6.0 - MedVL-SAM2: A unified 3D medical vision-language model for multimodal reasoning and prompt-driven segmentation
A unified 3D medical vision-language model for advanced multimodal reasoning and precise 3D segmentation.
Medical AIViability: 8.0 - Explainable Deep Learning for Pediatric Pneumonia Detection in Chest X-Ray Images
AI-based diagnostic tool for accurate pediatric pneumonia detection using explainable deep learning.
Medical AIViability: 8.0 - C-GRASP: Clinically-Grounded Reasoning for Affective Signal Processing
Develop a clinically-grounded AI tool for accurate heart rate variability interpretation in biomedical engineering.
Medical AIViability: 7.0 - LeMoF: Level-guided Multimodal Fusion for Heterogeneous Clinical Data
LeMoF provides a novel multimodal fusion framework enhancing clinical predictions from heterogeneous datasets like EHRs and biosignals.
Medical AIViability: 7.0 - How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series
A workflow to optimize downsampling of nEMG signals for efficient neuromuscular disease detection.
Medical AIViability: 6.0 - MedRedFlag: Investigating how LLMs Redirect Misconceptions in Real-World Health Communication
MedRedFlag enhances LLM safety in medical communication by curating a dataset for better redirection of misconceptions in patient queries.
Medical AIViability: 6.0 - Learning temporal embeddings from electronic health records of chronic kidney disease patients
Develop a tool for learning temporal embeddings from electronic health records to improve chronic kidney disease patient outcomes.
Medical AIViability: 7.0 - Fair-Eye Net: A Fair, Trustworthy, Multimodal Integrated Glaucoma Full Chain AI System
Develop Fair-Eye Net, an AI system for equitable glaucoma screening and follow-up using multimodal data integration.
Medical AIViability: 7.0 - EHR-RAG: Bridging Long-Horizon Structured Electronic Health Records and Large Language Models via Enhanced Retrieval-Augmented Generation
EHR-RAG enhances clinical prediction from long-horizon EHRs using advanced retrieval-augmented generation techniques.
Medical AIViability: 5.0 - MHub.ai: A Simple, Standardized, and Reproducible Platform for AI Models in Medical Imaging
MHub.ai is a standardized platform for deploying and reproducibly benchmarking AI models in medical imaging.
Medical AIViability: 7.0 - Handling Missing Modalities in Multimodal Survival Prediction for Non-Small Cell Lung Cancer
AI model for resilient multimodal survival prediction in NSCLC that handles missing modalities effectively.
Medical AIViability: 6.0 - A pipeline for enabling path-specific causal fairness in observational health data
A pipeline enabling path-specific causal fairness for machine learning models in healthcare to address biases.
Medical AIViability: 6.0 - Planner-Auditor Twin: Agentic Discharge Planning with FHIR-Based LLM Planning, Guideline Recall, Optional Caching and Self-Improvement
A Planner-Auditor framework enhances clinical discharge planning reliability using FHIR data and self-improvement loops.
Medical AIViability: 3.0 - ReaMIL: Reasoning- and Evidence-Aware Multiple Instance Learning for Whole-Slide Histopathology
ReaMIL enhances multiple instance learning in histopathology by efficiently selecting evidence while maintaining accuracy.
Medical AIViability: 4.0 - Conditioned Generative Modeling of Molecular Glues: A Realistic AI Approach for Synthesizable Drug-like Molecules
Develop AI-assisted drug designs to promote degradation of toxic proteins in Alzheimer's using molecular glues.
Medical AIViability: 6.0 - ctELM: Decoding and Manipulating Embeddings of Clinical Trials with Embedding Language Models
Develop an open-source framework for aligning language models with clinical trial embeddings for improved interpretability and generative use cases.
Medical AIViability: 6.0 - Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation
Medical SAM3 delivers a universal, prompt-driven segmentation model for medical imaging, solving domain shift challenges.
Medical AIViability: 9.0 - DEEPMED: Building a Medical DeepResearch Agent via Multi-hop Med-Search Data and Turn-Controlled Agentic Training & Inference
DeepMed enhances medical reasoning models by grounding in verifiable evidence and improving accuracy on medical benchmarks.
Medical AIViability: 6.0 - How Much Would a Clinician Edit This Draft? Evaluating LLM Alignment for Patient Message Response Drafting
AI-enhanced tool to augment clinician response drafting in patient portals by aligning LLM outputs with clinician preferences.
Medical AIViability: 7.0 - Topology-Guaranteed Image Segmentation: Enforcing Connectivity, Genus, and Width Constraints
Advanced image segmentation tool preserving topological attributes and width, ideal for medical imaging applications.
Medical AIViability: 7.0 - Self-learned representation-guided latent diffusion model for breast cancer classification in deep ultraviolet whole surface images
AI-powered breast cancer classification using synthetic data from advanced imaging.
Medical AIViability: 6.0 - MetaboNet: The Largest Publicly Available Consolidated Dataset for Type 1 Diabetes Management
MetaboNet offers a standardized, consolidated dataset for type 1 diabetes management, poised to become the benchmark for AI-driven diabetes intervention technologies.
Medical AIViability: 9.0 - DermaBench: A Clinician-Annotated Benchmark Dataset for Dermatology Visual Question Answering and Reasoning
Develop a dermatology visual question answering tool utilizing the DermaBench dataset for enhanced clinical decision support.
Medical AIViability: 8.0 - Towards Efficient and Robust Linguistic Emotion Diagnosis for Mental Health via Multi-Agent Instruction Refinement
APOLO boosts emotion analysis in mental health diagnostics with a multi-agent prompt optimization framework.
Medical AIViability: 8.0 - Organ-Aware Attention Improves CT Triage and Classification
Develop a CT triage system with organ-aware attention to improve radiology workflow efficiency.
Medical AIViability: 8.0 - CLEAR-Mamba:Towards Accurate, Adaptive and Trustworthy Multi-Sequence Ophthalmic Angiography Classification
Develop CLEAR-Mamba to enhance ophthalmic angiography classification's accuracy and reliability using hypernetworks and evidential uncertainty learning.
Medical AIViability: 7.0 - Decoder-Free Supervoxel GNN for Accurate Brain-Tumor Localization in Multi-Modal MRI
A novel graph-based method for accurate brain-tumor localization in multi-modal MRI using a decoder-free architecture.
Medical AIViability: 7.0 - Generalizing Abstention for Noise-Robust Learning in Medical Image Segmentation
Develop a noise-robust medical image segmentation tool using an abstention framework to improve accuracy in noisy datasets.
Medical AIViability: 7.0 - Who Should Have Surgery? A Comparative Study of GenAI vs Supervised ML for CRS Surgical Outcome Prediction
AI-powered tool for predicting surgical outcomes in chronic rhinosinusitis patients using a blend of ML and GenAI.
Medical AIViability: 7.0 - GeoDynamics: A Geometric State-Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
GeoDynamics offers a novel geometric state-space neural network customizing brain dynamics analysis on Riemannian manifolds for early disease detection.
Medical AIViability: 7.0 - ECG-Agent: On-Device Tool-Calling Agent for ECG Multi-Turn Dialogue
Develop on-device ECG dialogue agents capable of multi-turn interactions to improve cardiac diagnostics.
Medical AIViability: 7.0 - Automated Rubrics for Reliable Evaluation of Medical Dialogue Systems
Automated rubric generation for evaluating and refining medical dialogue systems.
Medical AIViability: 8.0 - Federated Transformer-GNN for Privacy-Preserving Brain Tumor Localization with Modality-Level Explainability
A federated learning platform for privacy-preserving brain tumor localization across healthcare institutions.
Medical AIViability: 8.0