Publications citing MIMIC-CXR Database v2.1.0

Z Visual-language foundation models for medical and clinical diagnosis and treatments
Haoran Guan, X. Chen, Chengxing Shen et al. The Visual Computer, 2025. Cites: dataset

Context-Aware Prompt Engineering and Time-Aware LLM Architecture for Radiology Report Generation
Mariem Medini, Riadh Bouslimi, Kaouther Nouira. IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), 2025. Cites: paper

Generative Counterfactual Augmentation for Bias Mitigation
Jason Uwaeze, Pranav Kulkarni, Vladimir Braverman et al. IEEE International Conference on Computer Vision Workshops, 2025. Cites: paper

MatSSL: Robust Self-Supervised Representation Learning for Metallographic Image Segmentation
Hoang Hai Nam Nguyen, Phan Nguyen Duc Hieu, Ho Won Lee. IEEE International Conference on Computer Vision Workshops, 2025. Cites: paper

Semantics Versus Identity: A Divide-and-Conquer Approach Towards Adjustable Medical Image De-Identification
Yuan Tian, Shuo Wang, Rongzhao Zhang et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2025. Cites: paper

Understanding Dataset Bias in Medical Imaging: A Case Study on Chest X-rays
Ethan Dack, Chengliang Dai. IEEE International Conference on Computer Vision Workshops, 2025. Cites: paper

A systematic review of multi-modal large language models on domain-specific applications
Sirui Li, Kok Wai Wong, Guanjin Wang et al. Artificial Intelligence Review, 2025. Cites: paper

RankRRG: A Rank-Aware Framework for Automated Radiology Report Generation
Meiyu Qiu, Yun Li, Xiaomao Fan et al. Lecture notes in computer science, 2025. Cites: paper

“Radiobiometrics”: Deep-learning radiograph biometrics for patient identification
Alistair Yap, Kyongtae T. Bae. Computers in Biology and Medicine, 2025. Cites: paper

Foundation Model for Medical Imaging: A Comprehensive Review
Licheng Jiao, Jingyi Yang, Ruiyang Li et al. IEEE Transactions on Artificial Intelligence, 2025. Cites: paper

Graph-Driven Medical Report Generation with Adaptive Knowledge Distillation
Jingqian Chen, Xin Huang, Mingfeng Jiang et al. Applied Sciences, 2025. Cites: paper

Three stylized light bulb illustrations are arranged in a row. The central bulb is yellow, while the two outer bulbs are dark blue. Each bulb is surrounded by small lines, suggesting illumination. The design is simple and uses a minimal color palette. Lamps: Learning Anatomy from Multiple Perspectives via Self-supervision in Chest Radiographs
Ziyu Zhou, Haozhe Luo, Mohammad Reza Hosseinzadeh Taher et al. Lecture notes in computer science, 2025. Cites: paper

From Pathology to Radiology: Evaluating the Applicability of Pathology Foundation Models
Hyun Yang, Sumin Jung, Jin Tae Kwak. Lecture notes in computer science, 2025. Cites: paper

Mind the Evaluation Gap: Large Language Models for Structured Data Extraction from Radiology Reports
Amirhossein Sabour, Kailin Chu, Mehrdad Eshraghi Dehaghani et al. Lecture notes in computer science, 2025. Cites: paper

Specialised or Generic? Tokenization Choices for Radiology Language Models
Hermione Warr, Wentian Xu, Harry Anthony et al. Lecture notes in computer science, 2025. Cites: paper

DC-RRG: Diagnosis-centered cascaded radiology report generation
Zihao Lin, Zinan Hong, Zijian Zhou et al. Expert Systems with Applications, 2025. Cites: paper

Development of a large-scale grounded vision language dataset for chest CT analysis
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao et al. Scientific Data, 2025. Cites: paper

Inference enhanced model with answer refinement for medical visual question answering
Yong Li, Zhenguo Yang, Lap–Kei Lee et al. Multimedia Systems, 2025. Cites: paper

Trends and applications of variational autoencoders in medical imaging analysis
Pauline Shan Qing Yeoh, Khairunnisa Binti Hasikin, Xiang Wu et al. Computerized Medical Imaging and Graphics, 2025. Cites: paper

A Survey on Medical Document Summarization: From Machine Learning Techniques to Large Language Models
Akash Ghosh, Raghav Jain, Anubhav Jhangra et al. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery, 2025. Cites: paper

Generative AI in depth: A survey of recent advances, model variants, and real-world applications
Shamim Yazdani, Akansha Singh, Nripsuta Ani Saxena et al. Journal Of Big Data, 2025. Cites: paper

A survey on electronic health record driven multimodal representation learning
Yutao Dou, Yaoyu Liu, Haitao Zou et al. Information Fusion, 2025. Cites: paper

Quantitative assessment of impact of technical and population-based factors on fairness of AI models for chest X-ray scans
Dmitry Cherezov, Pingfu Fu, Anant Madabhushi. Computers in Biology and Medicine, 2025. Cites: paper

ACFormer: A Multimodal Attention and Contrastive Learning Framework for Chest Disease Risk Prediction
Tao Lin, Yiheng Zhang. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics, 2025. Cites: paper

Align Modalities: Advancing Medical Report Generation with Unified Encoder and Inter-Case Contrastive Learning
Haoquan Chen, Mingtao Pei, Zhengang Nie. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics, 2025. Cites: paper

A Triplet Optimization and Difference Detail Perception Network with Adaptive Feature Enhancement for Radiology Report Generation
Yijie Zeng, Zhen Zhang, Wenfeng Jiang et al. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics, 2025. Cites: paper

Diffusion-based Data Augmentation via Noise Concatenation for Chest X-Ray Classification
Xinran Chen, Yujing Xin, Ning Liu et al. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics, 2025. Cites: paper

Multi-scale based cross-modal semantic alignment network for radiology report generation
Zhihao Zhang, Long Zhao, Dun Lan et al. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics, 2025. Cites: paper

Scaling down, Powering up: A Survey on the Advancements of Small Vision-Language Models
Sheikh Iftekhar Ahmed, Muhammad Zubair Hasan, Abrar Jahin Niloy et al. Information Fusion, 2025. Cites: paper

Cross-Species Disease Detection Model Using Domain Adaptation
Jeewon Kim. 2025. Cites: paper

Medical multimodal large language models: A systematic review
Yuan Hu, Chenhan Xu, Lin Bo et al. Intelligent Oncology, 2025. Cites: paper

Multi-label Classification of Chest X-ray Images: A Privacy-Preserving Method with Federated Learning
Madhuri Wakode, Geetanjali Kale. Lecture notes in networks and systems, 2025. Cites: paper

Avaliação da quantização de modelos visuais de linguagem para implantação em ambiente hospitalar
Rafael Scalabrin Dosso, Diedre Santos do Carmo, Letícia Rittner. SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2025. Cites: paper

Experience-guided multi-agent interpretable framework for radiology report summarization
Jia Li, Tong Zhou, Zichun Zhou et al. Computer Methods and Programs in Biomedicine, 2025. Cites: paper

Framework para avaliação de fairness em modelos de classificação aplicados à saúde
Letícia Lopes Mendes da Silva, Diedre Santos do Carmo, Letícia Rittner. SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI), 2025. Cites: paper

Structuring and Re-textualizing Breast MRI Reports Using Large Language Models
Koji Sakai, Tomohiro Kajikawa. Lecture notes on data engineering and communications technologies, 2025. Cites: paper

Silicodata: An Annotated Benchmark CXR Dataset for Silicosis Detection
Yasmeena Akhter, Rishabh Ranjan, Mayank Vatsa A et al. Scientific Data, 2025. Cites: paper

Deep learning in abdominopelvic digital subtraction angiography: a systematic review of interventional radiology applications
Daniel Raskin, Eyal Klang, Yiftach Barash et al. European Journal of Radiology, 2025. Cites: paper

Knowledge distillation and teacher–student learning in medical imaging: Comprehensive overview, pivotal role, and future directions
Xiang Li, Like Li, Minglei Li et al. Medical Image Analysis, 2025. Cites: paper

Enabling PSO-Secure Synthetic Data Sharing Using Diversity-Aware Diffusion Models
Mischa Dombrowski, Bernhard Kainz. Lecture notes in computer science, 2025. Cites: paper

Enhancing medical image report generation using a self-boosting multimodal alignment framework
Aqib Nazir Mir, Danish Raza Rizvi, Iqra Nissar. Health Information Science and Systems, 2025. Cites: paper

From Scope to Script: An Automated Report Generation Model for Gastrointestinal Endoscopy
Evandros Kaklamanos, Kristjana Kristinsdottir, Jonathan Huang et al. Lecture notes in computer science, 2025. Cites: paper

Pixel Perfect MegaMed: A Megapixel-Scale Vision-Language Foundation Model for Generating High Resolution Medical Images
Zahra TehraniNasab, Hujun Ni, Amar Kumar et al. Lecture notes in computer science, 2025. Cites: paper

A survey for large language models in biomedicine
Chong Wang, Mengyao Li, Junjun He et al. Artificial Intelligence in Medicine, 2025. Cites: paper

Refining medical large language models: key insights from instruction tuning
Muneerah Q. Alqahtani, Abdullah A. Al-Barakati, Fahd Saleh Alotaibi. PeerJ Computer Science, 2025. Cites: paper

State of the Art in Automatic Generation of Medical Reports: Models, Applications and Challenges
Bryan Vásquez-Pineda, Nicole Velasco-Molina, Yakdiel Rodríguez-Gallo. IEEE Central America and Panama Student Conference (CONESCAPAN), 2025. Cites: paper

Adapting and Evaluating Multimodal Large Language Models for Adolescent Idiopathic Scoliosis Self-management: A Divide and Conquer Framework
Zhaolong Wu, Pu Luo, Jason Pui Yin Cheung et al. Lecture notes in computer science, 2025. Cites: paper

Aligning Multimodal Large Language Models with Patient-Physician Dialogues for AI-Assisted Clinical Support
Junyong Lee, Jeihee Cho, Jiwon Ryu et al. Lecture notes in computer science, 2025. Cites: paper

Beyond One Size Fits All: Customization of Radiology Report Generation Methods
Tom van Sonsbeek, Arnaud A. A. Setio, Jung Oh Lee et al. Lecture notes in computer science, 2025. Cites: paper

CLIP-XRad: Learning Multimodal Representations of Chest X-Rays Through Contrastive Pretraining with Medical Concept Alignment
Tudor-Octavian Mihăiţă. International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2025. Cites: paper

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