Publications citing MIMIC-CXR Database v2.1.0

Artificial Intelligence Techniques to Predict the Airway Disorders Illness: A Systematic Review
Apeksha Koul, Rajesh K. Bawa, Yogesh Kumar. Archives of Computational Methods in Engineering, 2022. Cites: paper

Visual Transformers and Convolutional Neural Networks for Disease Classification on Radiographs: A Comparison of Performance, Sample Efficiency, and Hidden Stratification
Zachary R. Murphy, Kesavan Venkatesh, Jeremias Sulam et al. Radiology Artificial Intelligence, 2022. Cites: paper

Integrated multimodal artificial intelligence framework for healthcare applications
Luis R. Soenksen, Yu Ma, Cynthia Zeng et al. npj Digital Medicine, 2022. Cites: paper

Multi-Modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training
Jong Hak Moon, Hyungyung Lee, Woncheol Shin et al. IEEE Journal of Biomedical and Health Informatics, 2022. Cites: paper

Automatic captioning for medical imaging (MIC): a rapid review of literature
Djamila Romaissa Beddiar, Mourad Oussalah, Tapio Seppänen. Artificial Intelligence Review, 2022. Cites: paper

Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning
Ekin Tiu, Ellie Talius, Pujan R. Patel et al. Nature Biomedical Engineering, 2022. Cites: paper

Multimodal biomedical AI
Julián Acosta, Guido J. Falcone, Pranav Rajpurkar et al. Nature Medicine, 2022. Cites: paper

Image Embeddings Extracted from CNNs Outperform Other Transfer Learning Approaches in Classification of Chest Radiographs
Noemi Gozzi, Edoardo Giacomello, Martina Sollini et al. Diagnostics, 2022. Cites: paper

Survey on natural language processing in medical image analysis.
Zhengliang Liu, Mengshen He, Zuowei Jiang et al. PubMed, 2022. Cites: paper

Artificial Intelligence-Based Medical Data Mining
Amjad Zia, Muzzamil Aziz, Ioana Popa et al. Journal of Personalized Medicine, 2022. Cites: paper

Development and validation of an abnormality-derived deep-learning diagnostic system for major respiratory diseases
Chengdi Wang, Jiechao Ma, Shu Zhang et al. npj Digital Medicine, 2022. Cites: paper

Database and AI Diagnostic Tools Improve Understanding of Lung Damage, Correlation of Pulmonary Disease and Brain Damage in COVID-19
Ilona Sylwia Karpiel, Ana Starčević, Mirella Urzeniczok. Sensors, 2022. Cites: paper

Code and Data Sharing Practices in the Radiology Artificial Intelligence Literature: A Meta-Research Study
Kesavan Venkatesh, Samantha M. Santomartino, Jeremias Sulam et al. Radiology Artificial Intelligence, 2022. Cites: paper

DuETNet: Dual Encoder based Transfer Network for thoracic disease classification
Min Seok Lee, Sung Won Han. Pattern Recognition Letters, 2022. Cites: paper

Innovations in thoracic imaging: CT , radiomics, AI and x‐ray velocimetry
Rozemarijn Vliegenthart, Andreas Fouras, Colin Jacobs et al. Respirology, 2022. Cites: paper

Predicting Patient Demographics From Chest Radiographs With Deep Learning
Jason Adleberg, Amr H. Wardeh, Florence Xini Doo et al. Journal of the American College of Radiology, 2022. Cites: paper

BRAX, Brazilian labeled chest x-ray dataset
Eduardo Pontes Reis, Joselisa Péres Queiroz de Paiva, Maria Carolina Bueno da Silva et al. Scientific Data, 2022. Cites: paper

Moving from ImageNet to RadImageNet for Improved Transfer Learning and Generalizability
Alexandre Cadrin-Chênevert. Radiology Artificial Intelligence, 2022. Cites: paper

Addressing fairness in artificial intelligence for medical imaging
María Agustina Ricci Lara, Rodrigo Echeveste, Enzo Ferrante. Nature Communications, 2022. Cites: paper

Novel Coronavirus and Common Pneumonia Detection from CT Scans Using Deep Learning-Based Extracted Features
Ghazanfar Latif, Hamdy Morsy, Asmaa Hassan et al. Viruses, 2022. Cites: paper

Deployment and validation of an AI system for detecting abnormal chest radiographs in clinical settings
Ngoc Huy Nguyen, Ha Q. Nguyen, Nghia T. Nguyen et al. Frontiers in Digital Health, 2022. Cites: paper

External validation based on transfer learning for diagnosing atelectasis using portable chest X-rays
Xiaxuan Huang, Baige Li, Tao Huang et al. Frontiers in Medicine, 2022. Cites: paper

VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
Ha Q. Nguyen, Khanh Lam, Linh T. Le et al. Scientific Data, 2022. Cites: paper

Simplified Transfer Learning for Chest Radiography Models Using Less Data
Andrew Sellergren, Christina Chen, Zaid Nabulsi et al. Radiology, 2022. Cites: paper

Effect of pre-training scale on intra- and inter-domain, full and few-shot transfer learning for natural and X-Ray chest images
Mehdi Cherti, Jenia Jitsev. International Joint Conference on Neural Networks (IJCNN), 2022. Cites: paper

Artificial Intelligence in the Diagnosis of Diseases of the Respiratory System
Leticia M. Seijas, Byron Leite Dantas Bezerra. BENTHAM SCIENCE PUBLISHERS eBooks, 2022. Cites: paper

Developing an Artificial Intelligence Model for Reading Chest X-rays: Protocol for a Prospective Validation Study
Queralt Miró Catalina, Aïna Fuster‐Casanovas, Jordi Solé‐Casals et al. JMIR Research Protocols, 2022. Cites: paper

Developing and Validating Multi-Modal Models for Mortality Prediction in COVID-19 Patients: a Multi-center Retrospective Study
Joy Tzung-Yu Wu, Miguel Ángel Armengol de la Hoz, Po‐Chih Kuo et al. Journal of Imaging Informatics in Medicine, 2022. Cites: paper

Data-Efficient Vision Transformers for Multi-Label Disease Classification on Chest Radiographs
Finn Behrendt, Debayan Bhattacharya, Julia Krüger et al. Current Directions in Biomedical Engineering, 2022. Cites: paper

A contrastive triplet network for automatic chest X-ray reporting
Yan Qin Yang, Jun Yang Yu, Hanliang Jiang et al. Neurocomputing, 2022. Cites: paper

REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays
Ricardo Bigolin Lanfredi, Mingyuan Zhang, William F. Auffermann et al. Scientific Data, 2022. Cites: dataset, paper

Diagnostic captioning: a survey
John Pavlopoulos, Vasiliki Kougia, Ion Androutsopoulos et al. Knowledge and Information Systems, 2022. Cites: paper

Precision medical image hash retrieval by interpretability and feature fusion
Anna Guan, Li Liu, Xiaodong Fu et al. Computer Methods and Programs in Biomedicine, 2022. Cites: paper

A Survey on Data-driven COVID-19 and Future Pandemic Management
Yudong Tao, Chuang Yang, Tianyi Wang et al. ACM Computing Surveys, 2022. Cites: paper

Knowledge matters: Chest radiology report generation with general and specific knowledge
Shuxin Yang, Xian Wu, Shen Ge et al. Medical Image Analysis, 2022. Cites: paper

Clinical Comparable Corpus Describing the Same Subjects with Different Expressions
Yuta Nakamura, Shouhei Hanaoka, Yukihiro Nomura et al. Studies in health technology and informatics, 2022. Cites: paper

Performance of a Chest Radiograph AI Diagnostic Tool for COVID-19: A Prospective Observational Study
Ju Sun, Le Peng, Taihui Li et al. Radiology Artificial Intelligence, 2022. Cites: paper

Radiology Text Analysis System (RadText): Architecture and Evaluation
Song Wang, Mingquan Lin, Ying Ding et al. IEEE International Conference on Healthcare Informatics (ICHI), 2022. Cites: paper

Reply to: ‘Potential sources of dataset bias complicate investigation of underdiagnosis by machine learning algorithms’ and ‘Confounding factors need to be accounted for in assessing bias by machine learning algorithms’
Laleh Seyyed-Kalantari, Haoran Zhang, Matthew B. A. McDermott et al. Nature Medicine, 2022. Cites: paper

Who should do as AI say? Only non-task expert physicians benefit from correct explainable AI advice
Susanne Gaube, Harini Suresh, Martina Raue et al. Research Square, 2022. Cites: dataset

Computer-aided Diagnosis through Medical Image Retrieval in Radiology
Wilson Silva, Tiago Gonçalves, Kirsi Härmä et al. Research Square, 2022. Cites: paper

ThoraciNet: thoracic abnormality detection and disease classification using fusion DCNNs
Manav Gakhar, Apeksha Aggarwal. Physical and Engineering Sciences in Medicine, 2022. Cites: paper

Deep transfer learning to quantify pleural effusion severity in chest X-rays
Tao Huang, Rui Yang, Longbin Shen et al. BMC Medical Imaging, 2022. Cites: paper

Matching Visual Features to Hierarchical Semantic Topics for Image Paragraph Captioning
Dandan Guo, Ruiying Lu, Bo Chen et al. International Journal of Computer Vision, 2022. Cites: paper

Performance improvement in multi-label thoracic abnormality classification of chest X-rays with noisy labels
Mingyan Yang, Hisashi Tanaka, Takayuki Ishida. International Journal of Computer Assisted Radiology and Surgery, 2022. Cites: paper

Automatic Localization and Identification of Thoracic Diseases from Chest X-rays with Deep Learning
Xiaoyan Xin, Jian Zhang, Wei Wang et al. Current Medical Imaging Formerly Current Medical Imaging Reviews, 2022. Cites: paper

Validation of an Artificial Intelligence model for reading chest X-rays: protocol of a prospective study (Preprint)
Queralt Miró Catalina, Aïna Fuster‐Casanovas, Jordi Solé‐Casals et al. 2022. Cites: paper

Local Label Point Correction for Edge Detection of Overlapping Cervical Cells
Jiawei Liu, Huijie Fan, Qiang Wang et al. Frontiers in Neuroinformatics, 2022. Cites: paper

AI recognition of patient race in medical imaging: a modelling study
Judy Wawira Gichoya, Imon Banerjee, Ananth Reddy Bhimireddy et al. The Lancet Digital Health, 2022. Cites: paper

A survey on attention mechanisms for medical applications: are we moving towards better algorithms?
Tiago Gonçalves, Isabel Rio-Torto, Luís Filipe Teixeira et al. Research Square, 2022. Cites: paper

Cited by