Publications citing MIMIC-CXR Database v2.1.0

Genetic analysis of imaging-derived phenotypes
Yiming Bian, Joshua M. Akey. Nature Reviews Genetics, 2026. Cites: paper

Medical question answering: A comprehensive multimodal and LLM-driven survey
Eya Mhedhbi, Xiang Zhu, Muhammad Ayaz et al. Computer Methods and Programs in Biomedicine, 2026. Cites: paper

HiVLR: Hierarchical Vision-Language Reasoning for interpretable zero-shot radiography image understanding
Xilin Dang, Kang Li B, P Y Heng. Medical Image Analysis, 2026. Cites: paper

LiDAR: Liquid Delta-Aware Reporting Interpretable for Longitudinal Chest X-Rays
Anushka, Anshuman Shastri, Patrick S. P. Wang et al. International Journal of Pattern Recognition and Artificial Intelligence, 2026. Cites: paper

Rethinking Medical VQA Models: Towards Data-Efficient Learning
Shuning He, Da Ren, Haiwei Pan et al. Computational Visual Media, 2026. Cites: paper

A Latent Diffusion Model With Spatial Attributes for 3D Reconstruction in Biplanar X-Ray Images
Jingyi Bian, Deqiang Xiao, Teng Zhang et al. IEEE Transactions on Circuits and Systems for Video Technology, 2026. Cites: paper

AutoM3D: Multimodal Transformer-Based Disease Diagnosis from X-ray, Text, and EHR Data
Aditya Dubey, Shirish Mohan Dubey, Gaurav Sharma et al. International Conference on Computing, Intelligence, and Applications (CIACON), 2026. Cites: paper

Cross-Modal Adaptive Adversarial Defense for Medical Imaging with Explanation Stability
Gladys Wavinya Muoka, Wang Qingxian, Adeleye Idowu et al. Asia Conference on Machine Learning and Computing (ACMLC), 2026. Cites: paper

Deep Learning Driven Multi-Label Triage and Structured Reporting System for Classification of Tuberculosis and Pneumonia
U Sakthi, Aby Joseph, Akshita Choudhary. International Conference on Natural Language Processing and Computer Vision (ICNPCV), 2026. Cites: paper

Dual-View Vision Transformer with Cross-Modal Memory for Radiology Report Generation
Noureddine Lamred, Norhene Gargouri Ben Ayed, Nesrine Charfi. International Conference on Control, Decision and Information Technologies (CoDIT), 2026. Cites: paper

Hybrid Transfer Learning for Lung Disease Classification Integrating DeiT and EfficientNet for Inferencing and Training on Consumer Grade CPUs
Dhruv Narayan Raina, Rahul Deva. International Conference on Computational Intelligence Systems and Devices (ICCISD), 2026. Cites: paper

MUC-FL: Block-Wise Marginal Utility Contribution for Communication-Efficient Federated Learning
Akshay Mhatre, Vikram Karthick, Deepti Gupta et al. IEEE International Conference on Information Reuse and Integration (IRI), 2026. Cites: paper

Toward a Unified Multimodal Framework for Chest X-ray Analysis: A Hybrid Convolutional–State Space Approach
Adjia Ndeye Penda Dieng, Samawel Jaballi, Henri Nicolas et al. International Conference on Control, Decision and Information Technologies (CoDIT), 2026. Cites: paper

Assessing Utility-Leakage Trade-offs in Coreset Selection for Chest X-Ray Embeddings
Aldo Marzullo, Sebastián Andrés Cajas, Leo Anthony Celi et al. ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), 2026. Cites: paper

Multimodal Fusion and Adaptive Learning for Cardiopulmonary Classification
Mahjabeen Tamanna Abed, Xinghui Zhao. ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), 2026. Cites: paper

Encoding Versus Linear Use of Patient Characteristics in Chest X-Ray Foundation Models on MIMIC-CXR
Y I Kim, Yangwon Kim, Yoojin Nam et al. Diagnostics, 2026. Cites: paper

Multimodal precision diagnostics via cardionet+: fusing time-series, imaging, and knowledge graphs for cardiac risk modeling
Victor Adeyi Odeh, Zhang Xiaoling, Kuyikabasi Uko et al. Biomedical Signal Processing and Control, 2026. Cites: paper

Prediction of severe pediatric community-acquired pneumonia using multimodal fusion of chest radiographs and clinical data
Lianting Hu, Y I F E I Li, Mingzhao Huang et al. BMC Pediatrics, 2026. Cites: paper

Collaborative cross-modal fusion network for medical report generation
Xiaodi Hou, X J Li, Mingyu Lu et al. Information Fusion, 2026. Cites: paper

Evaluating the robustness and readiness of large frontier models in health AI applications
裕二池谷, Jingjing Fu, Xiaodong Liu et al. Nature Medicine, 2026. Cites: paper

Generalized Medical Phrase Grounding
Wenjian Zhang, Shekhar S. Chandra, Aaron Nicolson. IEEE Transactions on Medical Imaging, 2026. Cites: paper

Confidence-gated cloud-edge cascade triage via variational risk minimization for medical imaging
Xinye Yang, Zhusi Zhong, Scott Collins et al. Smart Health, 2026. Cites: paper

Disparate privacy risks from medical AI
Moritz A. Knolle, Martin J. Menten, Friederike Jungmann et al. Nature, 2026. Cites: paper

Generative AI for healthcare: fundamentals, challenges, and perspectives
Gang Chen, Changshuo Liu, Ooi Gene Anne et al. Science China Information Sciences, 2026. Cites: paper

How is Bias Learned in Medical Image Analysis Models? An Exploration of the Encoding of Demographic Information in Deep Learning Models Trained to Detect Abnormalities on Chest X-Rays
Nikhil Cherian Kurian, Phoenix Neale Williams, Sahar Abdulrahman et al. Journal of Imaging Informatics in Medicine, 2026. Cites: paper

Impact of Exposure Parameters on Deep Learning Models in Chest Radiography and Implications for Deployment
H. Shu, Shun-Ting Chang, Rodrigo Rosa Gameiro et al. Radiology Artificial Intelligence, 2026. Cites: paper

Federated learning for medical image analysis: Methods, challenges, and future directions
Thu Thuy Le, Phuong-Nam Tran, Nhat Truong Pham et al. Advanced Engineering Informatics, 2026. Cites: paper

A reliability-aware analytics framework for multi-vendor Tuberculosis screening from chest radiographs
Abu Salam, Pulung Nurtantio Andono, Purwanto et al. Healthcare Analytics, 2026. Cites: paper

Integrating augmentation-aware manifold smoothing and momentum-adjusted loss for handling class imbalance in thoracic disease detection
Sneha H.R, Basava Annappa. Frontiers in Medicine, 2026. Cites: paper

Automated radiology report generation: A comprehensive review
Lina Huang, Tasin Islam, Alina Miron et al. Expert Systems with Applications, 2026. Cites: paper

EC-RAG: Evidence-Centric Retrieval-Augmented Generation for Medical Visual Question Answering
Li S, Jun Long. International Conference on Multimedia Retrieval, 2026. Cites: paper

MMG-RAG: Multimodal Graph RAG for Medical Report Generation
Gang Liu, Xiaotian Tang, Jiacheng Gan et al. International Conference on Multimedia Retrieval, 2026. Cites: paper

Causal counterfactual simulation for treatment decisions in multimodal lung disease data
Yifei Zhu, Lei Zhang, Chris Sainsbury et al. Computers in Biology and Medicine, 2026. Cites: paper

An Explainable Multimodal AI Framework with Reinforcement Learning for Post-Surgical Clinical Decision Support
Mostak Ahmed, Faisal Ahmed, Shirajum Munira Mow et al. medRxiv, 2026. Cites: paper

Dual-path decoupling and contrastive hashing for medical cross-modal retrieval
Yuehua Chen, Can Liang, Renwei Xia et al. Pattern Recognition, 2026. Cites: paper

A locally deployable agentic framework for clinical data deidentification
Anja Hirsch, Foo Wei Ten, Kyle Steven Krueger et al. medRxiv, 2026. Cites: dataset

Multi-View Chest X-Ray Vision-Language Pre-Training via Semantic-Aware Masked Language Modeling and High-Order Alignment
Lihong Qiao, Jingya Gong, Yucheng Shu et al. IEEE Transactions on Medical Imaging, 2026. Cites: paper

On Multilingual Medical LLMs
Emine Ela Küçük, Dilek Küçük. Advances in computational intelligence and robotics book series, 2026. Cites: paper

Artificial intelligence in paediatric chest imaging: applications, challenges, and future directions
John Joseph Muringathuparambil, Shamiek Maharaj, Bradley Segal et al. Pediatric Radiology, 2026. Cites: paper

Continual Learning for Histopathology Image Classification in Class-Incremental Learning
Yuanyuan Wu, Yu Zhao, Anca Ralescu. Diagnostics, 2026. Cites: paper

Perineural Invasion Detection Using Deep Learning: A Systematic Review
Hayagreev Jeyandran, R. Veena. SN Computer Science, 2026. Cites: paper

A Lightweight Framework for Multi-view Chest Radiograph Analysis using Augmented Metadata
Sudipta Kumar Saha, Moutushe Basak Mimi, Abdullah All Ahhad et al. International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII), 2026. Cites: paper

AnatomiX, an Anatomy-Aware Grounded Multimodal Large Language Model for Chest X-Ray Interpretation
Anees Ur Rehman Hashmi, Numan Saeed, Christoph Lippert. 2026. Cites: paper

A survey on medical multimodal retrieval-augmented generation (RAG)
Ruipeng Wang, Jian Wang, Yan Huang et al. High-Confidence Computing, 2026. Cites: paper

A Word-Level Enhanced Method based on Position Embedding for Medical Image Captioning
Ziwei Tang, Chang Meng, Yang Wang et al. IEEE International Conference on Computer Vision and Deep Learning (DLCV), 2026. Cites: paper

Delrer: Disease Evolution-Informed Longitudinal Radiology Report Generation
Kaiyu Wang, Bing Wang, Changchun Li et al. 2026. Cites: paper

HGDC-Fuse: Clinical Multi-modal Fusion with Heterogeneous Graph and Disease Correlation Learning for Multi-Disease Prediction
Yueheng Jiang, Peng Zhang. International Joint Conference on Neural Networks (IJCNN), 2026. Cites: paper

If You Can Describe it, They Can See it: Cross-Modal Learning of Visual Concepts from Textual Descriptions
Carlo Alberto Barbano, Luca Molinaro, Massimiliano Ciranni et al. 2026. Cites: paper

LlamaRG: A Multi-View Large Language Model for Radiology Report Generation
Tanuja Jayas, Aditya Rastogi, Pavithra Raghavan et al. 2026. Cites: paper

Pathology Shortcuts: Detecting and Mitigating Reliance on Non-Target Pathologies in Chest X-ray AI
H. Shu, Shun-Ting Chang, Meng-Ping Huang et al. IEEE International Conference on Healthcare Informatics (ICHI), 2026. Cites: paper

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