Publications citing MIMIC-CXR Database v2.1.0

RadAdapt: Radiology Report Summarization via Lightweight Domain Adaptation of Large Language Models
Dave Van Veen, Cara Van Uden, Maayane Attias et al. Workshop on Biomedical Language Processing (BioNLP), 2023. Cites: paper

Relaxing Contrastiveness in Multimodal Representation Learning
Zudi Lin, Erhan Bas, Kunwar Yashraj Singh et al. IEEE Winter Conference on Applications of Computer Vision, 2023. Cites: paper

Robustness Stress Testing in Medical Image Classification
Mobarakol Islam, Zeju Li, Ben Glocker. Lecture notes in computer science, 2023. Cites: paper

shs-nlp at RadSum23: Domain-Adaptive Pre-training of Instruction-tuned LLMs for Radiology Report Impression Generation
Sanjeev Kumar Karn, Rikhiya Ghosh, P Kusuma et al. Workshop on Biomedical Language Processing (BioNLP), 2023. Cites: paper

Style-Aware Radiology Report Generation with RadGraph and Few-Shot Prompting
Benjamin Yan, Ruochen Liu, David E. Kuo et al. Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP), 2023. Cites: paper

TCSA: A Text-Guided Cross-View Medical Semantic Alignment Framework for Adaptive Multi-view Visual Representation Learning
Hongyang Lei, Huazhen Huang, Bokai Yang et al. Lecture notes in computer science, 2023. Cites: paper

The Role of Subgroup Separability in Group-Fair Medical Image Classification
Charles Jones, Mélanie Roschewitz, Ben Glocker. Lecture notes in computer science, 2023. Cites: paper

Toward Expanding the Scope of Radiology Report Summarization to Multiple Anatomies and Modalities
Zhihong Chen, Maya Varma, Xiang Wan et al. Annual Meeting of the Association for Computational Linguistics (ACL), 2023. Cites: paper

Using Multiple Instance Learning to Build Multimodal Representations
Peiqi Wang, William M. Wells, Seth Berkowitz et al. Lecture notes in computer science, 2023. Cites: paper

Utilizing Longitudinal Chest X-Rays and Reports to Pre-fill Radiology Reports
Qingqing Zhu, Tejas Sudharshan Mathai, Pritam Mukherjee et al. Lecture notes in computer science, 2023. Cites: paper

UTSA-NLP at RadSum23: Multi-modal Retrieval-Based Chest X-Ray Report Summarization
Tongnian Wang, Xingmeng Zhao, Anthony Rios. Workshop on Biomedical Language Processing (BioNLP), 2023. Cites: paper

Visual Grounding of Whole Radiology Reports for 3D CT Images
Akimichi Ichinose, Taro Hatsutani, Keigo Nakamura et al. Lecture notes in computer science, 2023. Cites: paper

Xplainer: From X-Ray Observations to Explainable Zero-Shot Diagnosis
Chantal Pellegrini, Matthias Keicher, Ege Özsoy et al. Lecture notes in computer science, 2023. Cites: paper

X-TRA: Improving Chest X-ray Tasks with Cross-Modal Retrieval Augmentation
Tom van Sonsbeek, Marcel Worring. Lecture notes in computer science, 2023. Cites: paper

You’ve Got Two Teachers: Co-evolutionary Image and Report Distillation for Semi-supervised Anatomical Abnormality Detection in Chest X-Ray
Jinghan Sun, Dong Wei, Zhe Xu et al. Lecture notes in computer science, 2023. Cites: paper

Machine Learning Model for Chest Radiographs: Using Local Data to Enhance Performance
Sarah F. Mohn, Marco Law, Maria Koleva et al. Canadian Association of Radiologists Journal, 2022. Cites: paper

Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionals
Kathrin Blagec, Kraiger Jakob, Wolfgang Fruehwirt et al. Journal of Biomedical Informatics, 2022. Cites: paper

PMFL: Partial Meta-Federated Learning for heterogeneous tasks and its applications on real-world medical records
Tianyi Zhang, Shirui Zhang, Ziwei Chen et al. IEEE International Conference on Big Data (BigData), 2022. Cites: dataset, paper

Radiopaths: Deep Multimodal Analysis on Chest Radiographs
Mohammad Kohankhaki, Ahmad Ayad, Mahdi Barhoush et al. IEEE International Conference on Big Data (BigData), 2022. Cites: paper

The Challenge Dataset – simple evaluation for safe, transparent healthcare AI deployment
James K. Sanayei, Mohamed Abdalla, Monish Ahluwalia et al. medRxiv, 2022. Cites: paper

A Survey on Tools and Techniques for Localizing Abnormalities in X-ray Images Using Deep Learning
Muhammad Aasem, Muhammad Javed Iqbal, Iftikhar A. Ahmad et al. Mathematics, 2022. Cites: paper

Domain-ensemble learning with cross-domain mixup for thoracic disease classification in unseen domains
Hongyu Wang, Yong Xia. Biomedical Signal Processing and Control, 2022. Cites: paper

Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis
Hirotaka Ieki, Kaoru Ito, Mike Saji et al. Communications Medicine, 2022. Cites: paper

PreRadE: Pretraining Tasks on Radiology Images and Reports Evaluation Framework
Matthew Coleman, Joanna F. Dipnall, Myong Chol Jung et al. Mathematics, 2022. Cites: paper

Clinically Coherent Radiology Report Generation with Imbalanced Chest X-rays
Hang Yu, Qingchen Zhang. IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022. Cites: paper

A Survey on AI Techniques for Thoracic Diseases Diagnosis Using Medical Images
Fatma A. Mostafa, Lamiaa A. Elrefaei, Mostafa M. Fouda et al. Diagnostics, 2022. Cites: dataset, paper

Artificial intelligence in veterinary diagnostic imaging: A literature review
Erin Hennessey, Matthew R. DiFazio, Ryan Hennessey et al. Veterinary Radiology & Ultrasound, 2022. Cites: paper

Computer-aided diagnosis through medical image retrieval in radiology
Wilson Silva, Tiago Gonçalves, Kirsi Härmä et al. Scientific Reports, 2022. Cites: paper

How Well Do Self-Supervised Models Transfer to Medical Imaging?
Jonah Anton, Liam Castelli, Mun Fai Chan et al. Journal of Imaging, 2022. Cites: paper

Learning Concept Credible Models for Mitigating Shortcuts.
Jiaxuan Wang, Sarah Jabbour, Maggie Makar et al. PubMed, 2022. Cites: paper

A comparative study of pretrained language models for long clinical text
Yikuan Li, Ramsey M. Wehbe, Faraz S. Ahmad et al. Journal of the American Medical Informatics Association, 2022. Cites: paper

Contrastive self-supervised learning from 100 million medical images with optional supervision
Florin C. Ghesu, Bogdan Georgescu, Awais Mansoor et al. Journal of medical imaging, 2022. Cites: paper

Self-Supervised Pretraining Enables High-Performance Chest X-Ray Interpretation Across Clinical Distributions
Niveditha S. Iyer, Aditya Gulati, Oishi Banerjee et al. medRxiv, 2022. Cites: paper

Detection of Pathologies in X-Ray Chest Images using a Deep Convolutional Neural Network with Appropriate Data Augmentation Techniques
Sebastián Quevedo, Federico Domínguez, Enrique Peláez. IEEE ANDESCON, 2022. Cites: paper

Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD
Giuseppe D’Ancona, Mauro Massussi, Mattia Savardi et al. International Journal of Cardiology, 2022. Cites: paper

Describe like a pathologist: Glomerular immunofluorescence image caption based on hierarchical feature fusion attention network
Haoran Liu, Lei Peng, Yongle Xie et al. Expert Systems with Applications, 2022. Cites: paper

Improving Medical X-ray Report Generation by Using Knowledge Graph
Dehai Zhang, Anquan Ren, Jiashu Liang et al. Applied Sciences, 2022. Cites: paper

Contractible Regularization for Federated Learning on Non-IID Data
Zifan Chen, Zhe Wu, Xian Wu et al. Proceedings, 2022. Cites: paper

RoS-KD: A Robust Stochastic Knowledge Distillation Approach for Noisy Medical Imaging
Ajay Kumar Jaiswal, Kumar Ashutosh, Justin F. Rousseau et al. Proceedings, 2022. Cites: paper

Total bilirubin is associated with all-cause mortality in patients with acute respiratory distress syndrome: a retrospective study
Zhoude Zheng, Zhen’ge Chang, Yuxiong Chen et al. Annals of Translational Medicine, 2022. Cites: paper

Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese
Thao Ngoc Nguyen, Tam M. Vo, Thắng Việt Nguyễn et al. PLoS ONE, 2022. Cites: paper

Artificial intelligence-based methods for fusion of electronic health records and imaging data
Farida Mohsen, Hazrat Ali, Nady El Hajj et al. Scientific Reports, 2022. Cites: paper

COVID-19 CXR Classification: Applying Domain Extension Transfer Learning and Deep Learning
KwangJin Park, Youngjin Choi, Hong-Chul Lee. Applied Sciences, 2022. Cites: paper

Weakly supervised thoracic disease localization via disease masks
Hong-Gyu Jung, Woo-Jeoung Nam, Hyunwoo Kim et al. Neurocomputing, 2022. Cites: paper

PCAN: Pixel-wise classification and attention network for thoracic disease classification and weakly supervised localization
Xiongfeng Zhu, Shumao Pang, Xiaoxuan Zhang et al. Computerized Medical Imaging and Graphics, 2022. Cites: paper

Event-Based Clinical Finding Extraction from Radiology Reports with Pre-trained Language Model
Wilson Lau, Kevin Lybarger, Martin L. D. Gunn et al. Journal of Imaging Informatics in Medicine, 2022. Cites: paper

Deploying deep learning models on unseen medical imaging using adversarial domain adaptation
Aly Al-Amyn Valliani, Faris F. Gulamali, Young Joon Kwon et al. PLoS ONE, 2022. Cites: paper

Self-supervised Model Based on Masked Autoencoders Advance CT Scans Classification
Jiashu Xu, Sergii Stirenko. International Journal of Image Graphics and Signal Processing, 2022. Cites: paper

MS-CheXNet: An Explainable and Lightweight Multi-Scale Dilated Network with Depthwise Separable Convolution for Prediction of Pulmonary Abnormalities in Chest Radiographs
Shashank Shetty, V. S. Ananthanarayana, Ajit Ramakant Mahale. Mathematics, 2022. Cites: paper

MIFTP: A Multimodal Multi-Level Independent Fusion Framework with Improved Twin Pyramid for Multilabel Chest X-Ray Image Classification
Jingni Zeng, Ke Niu, You Li Lu et al. IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2022. Cites: paper

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