Publications citing MIMIC-CXR Database v2.1.0

Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features
Ashkan Khakzar, Yang Zhang, Wejdene Mansour et al. Lecture notes in computer science, 2021. Cites: paper

IBMResearch at MEDIQA 2021: Toward Improving Factual Correctness of Radiology Report Abstractive Summarization
Diwakar Mahajan, Ching-Huei Tsou, Jennifer J. Liang. Workshop on Biomedical Language Processing (BioNLP), 2021. Cites: paper

Improving Factual Completeness and Consistency of Image-to-Text Radiology Report Generation
Yasuhide Miura, Yuhao Zhang, Emily B. Tsai et al. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), 2021. Cites: paper

Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region Alignment
Zhanghexuan Ji, Mohammad Abuzar Shaikh, Dana Moukheiber et al. Lecture notes in computer science, 2021. Cites: paper

Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam et al. Lecture notes in computer science, 2021. Cites: paper

Labeling Chest X-Ray Reports Using Deep Learning
Maram Mahmoud A. Monshi, Josiah Poon, Yuk Ying Chung et al. Lecture notes in computer science, 2021. Cites: paper

Linguistic Uncertainty in Clinical NLP: A Taxonomy, Dataset and Approach
Mark St. J. Turner, Julia Ive, Sumithra U. Velupillai. Lecture notes in computer science, 2021. Cites: paper

Multimodal Multitask Deep Learning for X-Ray Image Retrieval
Yang Yu, Peng Hu, Jie Lin et al. Lecture notes in computer science, 2021. Cites: paper

Multimodal Representation Learning via Maximization of Local Mutual Information
Ruizhi Liao, Daniel Moyer, Miriam Cha et al. Lecture notes in computer science, 2021. Cites: paper

Observational Supervision for Medical Image Classification Using Gaze Data
Khaled Kamal Saab, Sarah Hooper, Nimit S. Sohoni et al. Lecture notes in computer science, 2021. Cites: dataset

Out of Distribution Detection for Medical Images
Oliver R. Zhang, Jean-Benoit Delbrouck, Daniel L. Rubin. Lecture notes in computer science, 2021. Cites: paper

RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
Benjamin Hou, Georgios A. Kaissis, Ronald M. Summers et al. Lecture notes in computer science, 2021. Cites: dataset

Self-guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs
Constantin Seibold, Jens Kleesiek, Heinz‐Peter Schlemmer et al. Lecture notes in computer science, 2021. Cites: paper

Self-supervised Multi-modal Alignment for Whole Body Medical Imaging
Rhydian Windsor, Amir Jamaludin, Timor Kadir et al. Lecture notes in computer science, 2021. Cites: paper

Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models
Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger et al. Lecture notes in computer science, 2021. Cites: paper

Using Causal Analysis for Conceptual Deep Learning Explanation
Sumedha Singla, Stephen Wallace, Sofia Triantafillou et al. Lecture notes in computer science, 2021. Cites: paper

Variational Topic Inference for Chest X-Ray Report Generation
Ivona Najdenkoska, Xiantong Zhen, Marcel Worring et al. Lecture notes in computer science, 2021. Cites: paper

Domain specific word embeddings for natural language processing in radiology
Timothy L. Chen, Max Emerling, Gunvant Chaudhari et al. Journal of Biomedical Informatics, 2020. Cites: paper

Untitled
The Journal of Machine Learning for Biomedical Imaging, 2020. Cites: paper

Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays
Yan Han, Chongyan Chen, Liyan Tang et al. PubMed Central, 2020. Cites: paper

Discriminative ensemble learning for few-shot chest x-ray diagnosis
Angshuman Paul, Yuxing Tang, Thomas C. Shen et al. Medical Image Analysis, 2020. Cites: paper

Reinforced Medical Report Generation with X-Linear Attention and Repetition Penalty
Wenting Xu, Qi Chang, Zhenghua Xu et al. arXiv (Cornell University), 2020. Cites: paper

COVIDGR Dataset and COVID-SDNet Methodology for Predicting COVID-19 Based on Chest X-Ray Images
Siham Tabik, Anabel Gómez-Ríos, José Luis Martín Rodríguez et al. IEEE Journal of Biomedical and Health Informatics, 2020. Cites: paper

Proactive Construction of an Annotated Imaging Database for Artificial Intelligence Training
Caroline Bivik Stadler, Martin Lindvall, Claes F. Lundström et al. Journal of Imaging Informatics in Medicine, 2020. Cites: paper

COVID-19-CT-CXR: A Freely Accessible and Weakly Labeled Chest X-Ray and CT Image Collection on COVID-19 From Biomedical Literature
Yifan Peng, Yuxing Tang, Sungwon Lee et al. IEEE Transactions on Big Data, 2020. Cites: paper

The importance of standardisation – COVID-19 CT & Radiograph Image Data Stock for deep learning purpose
Krzysztof Misztal, Agnieszka Pocha, Martyna Durak-Kozica et al. Computers in Biology and Medicine, 2020. Cites: paper

A Survey on Deep Learning and Explainability for Automatic Image-based Medical Report Generation
Pablo Messina, Pablo Pino, Denis Parra et al. arXiv (Cornell University), 2020. Cites: paper

Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines
Shih-Cheng Huang, Anuj Pareek, Saeed Seyyedi et al. npj Digital Medicine, 2020. Cites: paper

Comparison of Chest Radiograph Interpretations by Artificial Intelligence Algorithm vs Radiology Residents
Joy Tzung-Yu Wu, Ken C. L. Wong, Yaniv Gur et al. JAMA Network Open, 2020. Cites: paper

Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes
Rachel Lea Draelos, David Dov, Maciej A. Mazurowski et al. Medical Image Analysis, 2020. Cites: paper

Contrastive Learning of Medical Visual Representations from Paired Images and Text
Yuhao Zhang, Hang Jiang, Yasuhide Miura et al. arXiv (Cornell University), 2020. Cites: paper

Self-Guided Multiple Instance Learning for Weakly Supervised Disease Classification and Localization in Chest Radiographs
Constantin Seibold, Jens Kleesiek, Heinz‐Peter Schlemmer et al. arXiv (Cornell University), 2020. Cites: paper

Learning Image Labels On-the-fly for Training Robust Classification Models
Xiaosong Wang, Ziyue Xu, Dong Yang et al. arXiv (Cornell University), 2020. Cites: paper

COVID19XrayNet: A Two-Step Transfer Learning Model for the COVID-19 Detecting Problem Based on a Limited Number of Chest X-Ray Images
Ruochi Zhang, Zhehao Guo, Yue Sun et al. Interdisciplinary Sciences Computational Life Sciences, 2020. Cites: paper

Artificial intelligence in radiology
Dakai Jin, Adam P. Harrison, Ling Zhang et al. Elsevier eBooks, 2020. Cites: paper

Deep hiearchical multi-label classification applied to chest X-ray abnormality taxonomies
Haomin Chen, Shun Miao, Daguang Xu et al. Medical Image Analysis, 2020. Cites: paper

Artificial Intelligence Solutions for Analysis of X-ray Images
Scott Adams, Robert D. E. Henderson, Yi Xin et al. Canadian Association of Radiologists Journal, 2020. Cites: paper

Classification of Multiple Diseases on Body CT Scans using Weakly Supervised Deep Learning
Fakrul Islam Tushar, Vincent M. D’Anniballe, Rui Hou et al. arXiv (Cornell University), 2020. Cites: paper

Multi-Disease Classification of 13,667 Body CT Scans Using Weakly Supervised Deep Learning
Fakrul Islam Tushar, Vincent M. D’Anniballe, Rui Hou et al. arXiv (Cornell University), 2020. Cites: paper

Weakly Supervised Multi-Organ Multi-Disease Classification of Body CT Scans.
Fakrul Islam Tushar, Vincent M. D’Anniballe, Rui Hou et al. arXiv (Cornell University), 2020. Cites: paper

Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
Hanan J. Farhat, George E. Sakr, Rima Kilany. Machine Vision and Applications, 2020. Cites: paper

Predicting COVID-19 Pneumonia Severity on Chest X-ray With Deep Learning
Joseph Cohen, Lan Dao, Karsten Roth et al. Cureus, 2020. Cites: paper

Position statement on priorities for artificial intelligence in GI endoscopy: a report by the ASGE Task Force
Tyler M. Berzin, Sravanthi Parasa, Michael B. Wallace et al. Gastrointestinal Endoscopy, 2020. Cites: paper

Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis
Agostina J. Larrazabal, Nicolás Nieto, Victoria Peterson et al. Proceedings of the National Academy of Sciences, 2020. Cites: paper

Deep learning in generating radiology reports: A survey
Maram Mahmoud A. Monshi, Josiah Poon, Yuk Ying Chung. Artificial Intelligence in Medicine, 2020. Cites: paper

Automated abnormality classification of chest radiographs using deep convolutional neural networks
Yuxing Tang, Yuxing Tang, Yifan Peng et al. npj Digital Medicine, 2020. Cites: paper

Supervised and unsupervised language modelling in Chest X-Ray radiological reports
Ignat A. Drozdov, Daniel Forbes, Benjamin Szubert et al. PLoS ONE, 2020. Cites: paper

Artificial Intelligence Explained for Nonexperts
Narges Razavian, Florian Knöll, Krzysztof J. Geras. Seminars in Musculoskeletal Radiology, 2020. Cites: paper

AI Accelerated Human-in-the-loop Structuring of Radiology Reports.
Joy Tzung-Yu Wu, Ali Syed, Hassan Ahmad et al. PubMed Central, 2020. Cites: paper

An Improved Marine Predators Algorithm With Fuzzy Entropy for Multi-Level Thresholding: Real World Example of COVID-19 CT Image Segmentation
Mohamed Abd Elaziz, Ahmed A. Ewees, Dalia Yousri et al. IEEE Access, 2020. Cites: paper

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