NeurIPS 2024PastLarge language modelsInterpretabilityHealthcare & biology
Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond
AIM-FM Workshop @ NeurIPS'24
- Submission deadline
- Sep 26, 2024, 23:59 UTCimported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Topics were auto-suggested and may be imprecise — edits welcome.
Accepted papers (81)
Fetched from OpenReview (v2) on 2026-06-10.
A Benchmark for Long-Form Medical Question Answering
A self-supervised framework for learning whole slide representations
A Self-Supervised Model for Multi-modal Stroke Risk Prediction
A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
Adaptive Reasoning and Acting in Medical Language Agents
An Autonomous Dual-channel Entity Recognition Method for Chinese Acupuncture
Anatomical 3D Style Transfer Enabling Efficient Federated Learning with Extremely Low Communication Costs
Application of Contrastive Learning on ECG Data: Evaluating Performance in Japanese and Classification with Around 100 Labels
Armadillo: Robust Secure Aggregation for Federated Learning with Input Validation
Assessment of Medical Foundation Models for Survival Prediction with Whole Slide Images
ASTRID - An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems
Best of Both Worlds: Harmonizing LLM Capabilities in Decision-Making and Question-Answering for Treatment Regimes
Biomedical SAM-2: Segment Anything in Biomedical Images and Videos
Catching the Spikes: Heteroscedastic Uncertainty Quantification for Enhanced Malaria Prediction
Cell Instance Segmentation with Large Vision Model for Circulating Aberrant Cells Identification through Fluorescence In Situ Hybridization Images
Cell ontology guided transcriptome foundation model
Classification of Melanoma Skin Cancer with Ensemble Learning and Stratified K-Fold Validation
Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases
Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status
Data Adaptive Few-shot Multi-label Segmentation with Foundation Model
DAug: Diffusion-based Channel Augmentation for Radiology Image Retrieval and Classification
Deep Generative Models Unveil Patterns in Medical Images Through Vision- “Language” Conditioning
Demographic Bias of Expert-Level Vision-Language Foundation Models in Medical Imaging
Development and bilingual evaluation of Japanese medical large language model within reasonably low computational resources
DiversityMedQA: A Benchmark for Assessing Demographic Biases in Medical Diagnosis using Large Language Models
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning using Packed Secret Sharing
Do Histopathological Foundation Models Eliminate Batch Effects? A Comparative Study
Do Large Language Models have Shared Weaknesses in Medical Question Answering?
Enhancing Interpretability and Fairness in Medical Foundation Models: A Generative Approach for Explainable and Bias-Mitigated Medical Image Analysis
Enhancing Medical NLP Systems: Integrating Upstash Vector and BGE-M3 for Accurate and Ethical Healthcare Data Management with Reduced Bias
Enhancing Trust in AI-Driven Dermatology: CLIP for Explainable Skin Lesion Diagnosis
Explaining Chest X-ray Pathology Models using Textual Concepts
Explaining Clusters Using Minimal Weighted Edge Coverage
Exploring Fairness in Long-Term Prediction of Type 2 Diabetes Microvascular Complications
Fairness Of AI Models in vector embedded Chest X-ray representations
Federated Self-Supervised Single-cell Clustering of scRNA-seq Data
Gaze-Assisted Medical Image Segmentation
Generative AI in the Hospital: A Participatory Assessment of Healthcare Needs and Challenges
Going beyond H&E and Oncology: how do Histopathology Foundation Models perform for multi-stain IHC & Immunology?
GPT Sonograpy: Hand Gesture Decoding from Forearm Ultrasound Images via VLM
Hetero-UNet: Heterogeneous Transformer with Mamba for Medical Image Segmentation
How Does Diverse Interpretability of Textual Prompts Impact Medical Vision-Language Zero-Shot Tasks?
Improving the Classification Effect of Clinical Images of Diseases for Multi-Source Privacy Protection
Integrating Image Interpretation and Textual Context for Improved Breast Imaging Classification
Intraoperative Glioma Segmentation with YOLO + SAM for Improved Accuracy in Tumor Resection
JRadiEvo: A Japanese Radiology Report Generation Model Enhanced by Evolutionary Optimization of Model Merging
Learning biologically relevant features in a pathology foundation model using sparse autoencoders
Leveraging Multimodal Machine Learning for Predictive Diagnostics of Adolescent Mental Health Disorders
Lung-DETR: Deformable Detection Transformer for Sparse Lung Nodule Anomaly Detection
M3H: Multimodal Multitask Machine Learning for Healthcare
MambaHealth: A Lightweight Foundation Model for Efficient Drug Recommendation
Masked Modeling for Single-cell Clustering of scRNA‐seq Data
Med-FastSAM: Improving Transfer Efficiency of SAM to Domain-Generalised Medical Image Segmentation
Medical Imaging Complexity and its Effects on GAN Performance
MediConfusion: Can you trust your AI radiologist? Probing the reliability of multimodal medical foundation models
MSA-LM: Integrating DNA-level Inductive Biases into DNA Language Models
Multimodal Lego: Model Merging and Fine-Tuning Across Topologies and Modalities
Necessity of Uncertainty Quantification for Audio-driven Healthcare Diagnosis
Neural machine translation of clinical procedure codes for medical diagnosis and uncertainty quantification
PATIENT-Ψ: Using Large Language Models to Simulate Patients for Training Mental Health Professionals
PICASO: Secure Aggregation for Federated Learning with Minimal Synchronization
Precise Lens Status Classification via Projection Tuning for Efficient Adaptation to Data Shifts in Small Cataract Image Datasets
ProMISe: Promptable Medical Image Segmentation using SAM
Promoting cross-modal representations to improve multimodal foundation models for physiological signals
QViSTA: A Novel Quantum Vision Transformer for Early Multi-Stage Alzheimer’s Diagnosis Using Optimized Variational Quantum Circuits
Random Token Fusion for Multi-View Medical Diagnosis
Reliability in AI-Assisted Critical Care: Assessing Large Language Model Robustness and Instruction Following for Cardiac Arrest Identification
Research Journey of Generative Protein Modeling
RespLLM: Unifying Audio and Text with Multimodal LLMs for Generalized Respiratory Health Prediction
SAM-MPA: Applying SAM to Few-shot Medical Image Segmentation using Mask Propagation and Auto-prompting
Sentiment Reasoning for Healthcare
Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning
Surgical-LLaVA: Toward Surgical Scenario Understanding via Large Language and Vision Models
Synthetic Multimodal Data Generation and Training Optimization For Computed Tomography Cardiac Imaging Applications
Towards a Personal Health Large Language Model
Towards Foundation Models for Critical Care Time Series
Training Free Adaptive Text Classification through Aggregated Large Language Models
TTT-UNet: Enhancing U-Net with Test-Time Training Layers for Biomedical Image Segmentation
Universal Speech Disorder Recognition: Towards a Foundation Model for Cross-Pathology Generalisation
VidLPRO: A Video-Language Pre-training Framework for Robotic and Laparoscopic Surgery
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