Publications citing MIMIC-CXR Database v2.1.0

BI-RADS BERT and Using Section Segmentation to Understand Radiology Reports
Grey Kuling, Belinda N. Curpen, Anne Louise Martel. Journal of Imaging, 2022. Cites: paper

Federated Learning for Electronic Health Records
Trung Kien Dang, Lan Xiang, Jianshu Weng et al. ACM Transactions on Intelligent Systems and Technology, 2022. Cites: paper

Evaluating Explainable Artificial Intelligence for X-ray Image Analysis
Miquel Miró-Nicolau, Gabriel Moyà-Alcover, Antoni Jaume-i-Capó. Applied Sciences, 2022. Cites: paper

Machine Deep Learning: Convolutional Neural Network-Application for Pectus Excavatum Diagnosis from Frontal-View Chest X-Rays
Yu-Jiun Fan, I‐Shiang Tzeng, Yuan‐Yu Hsu et al. Research Square, 2022. Cites: paper

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients
Daniel Gourdeau, Olivier Potvin, Jason Henry Biem et al. Scientific Reports, 2022. Cites: paper

Co-occurring diseases heavily influence the performance of weakly supervised learning models for classification of chest CT
Fakrul Islam Tushar, Vincent M. D’Anniballe, Geoffrey D. Rubin et al. SPIE Medical Imaging: Computer-Aided Diagnosis, 2022. Cites: paper

Incorporate radiograph-reading behavior and knowledge into deep reinforcement learning for lesion localization
Degan Hao, Dooman Arefan, Shandong Wu. SPIE Medical Imaging: Computer-Aided Diagnosis, 2022. Cites: paper

Demonstrating the Risk of Imbalanced Datasets in Chest X-Ray Image-Based Diagnostics by Prototypical Relevance Propagation
Srishti Gautam, Marina Höhne, Stine Hansen et al. IEEE International Symposium on Biomedical Imaging (ISBI), 2022. Cites: paper

Indication as Prior Knowledge for Multimodal Disease Classification in Chest Radiographs with Transformers
Grzegorz Jacenków, Alison Q. O’Neil, Sotirios A. Tsaftaris. IEEE International Symposium on Biomedical Imaging (ISBI), 2022. Cites: paper

Development of CNN models for the enteral feeding tube positioning assessment on a small scale data set
Gongbo Liang, Halemane S. Ganesh, Dylan Steffe et al. BMC Medical Imaging, 2022. Cites: paper

Review on approaches to concept detection in medical images
Diana Miranda, Veena Thenkanidiyoor, Dileep Aroor Dinesh. Journal of Applied Biomedicine, 2022. Cites: paper

A Systematic Review of Deep Learning Techniques for Tuberculosis Detection From Chest Radiograph
Mustapha Oloko-Oba, Serestina Viriri. Frontiers in Medicine, 2022. Cites: paper

Application of Artificial Intelligence in Lung Cancer
Hwa‐Yen Chiu, Heng‐Sheng Chao, Yuh‐Min Chen. Cancers, 2022. Cites: paper

VinDr-PCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children
Ngọc Hải Nguyễn, Huy‐Hieu Pham, Thanh T. Tran et al. medRxiv, 2022. Cites: paper

Deep Learning applications to detect pneumonia on chest X-ray: A systematic study
Neenu Sebastian, B. Ankayarkanni. International Conference on Advanced Computing Technologies and Applications (ICACTA), 2022. Cites: paper

Künstliche Intelligenz: Infrastrukturen und Voraussetzungen auf europäischer Ebene
Sebastian Johannes Fritsch, Oliver Maaßen, Morris Riedel. AINS - Anästhesiologie · Intensivmedizin · Notfallmedizin · Schmerztherapie, 2022. Cites: paper

Combining chest X-rays and electronic health record (EHR) data using machine learning to diagnose acute respiratory failure
Sarah Jabbour, David F. Fouhey, Ella Annabelle Kazerooni et al. Journal of the American Medical Informatics Association, 2022. Cites: paper

Radiological Analysis of COVID-19 Using Computational Intelligence: A Broad Gauge Study
S. Vineth Ligi, Soumya Snigdha Kundu, R. Kumar et al. Journal of Healthcare Engineering, 2022. Cites: paper

ImageGCN: Multi-Relational Image Graph Convolutional Networks for Disease Identification With Chest X-Rays
Chengsheng Mao, Liang Yao, Yuan Luo. IEEE Transactions on Medical Imaging, 2022. Cites: paper

Augmenting existing deterioration indices with chest radiographs to predict clinical deterioration
Emily Mu, Sarah Jabbour, Adrian Vasile Dalca et al. PLoS ONE, 2022. Cites: paper

Beyond Medical Imaging - A Review of Multimodal Deep Learning in Radiology
Lars Heiliger, Anjany Sekuboyina, Bjoern H. Menze et al. 2022. Cites: paper

Beyond Medical Imaging - A Review of Multimodal Deep Learning in Radiology
Lars Heiliger, Anjany Sekuboyina, Bjoern H. Menze et al. 2022. Cites: dataset, paper

Incorporating uncertainty in learning to defer algorithms for safe computer-aided diagnosis
Jessie Liu, Blanca Gallego, Sebastiano Barbieri. Scientific Reports, 2022. Cites: paper

A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images
Pablo Messina, Pablo Pino, Denis Parra et al. ACM Computing Surveys, 2022. Cites: paper

Generalized radiograph representation learning via cross-supervision between images and free-text radiology reports
Hong-Yu Zhou, Xiaoyu Chen, Yinghao Zhang et al. Nature Machine Intelligence, 2022. Cites: paper

Objective evaluation of deep uncertainty predictions for COVID-19 detection
Hamzeh Asgharnezhad, Afshar Shamsi, Roohallah Alizadehsani et al. Scientific Reports, 2022. Cites: paper

Deep learning prediction of sex on chest radiographs: a potential contributor to biased algorithms
David Li, Cheng Ting Lin, Jeremias Sulam et al. Emergency Radiology, 2022. Cites: paper

Segmentation and classification on chest radiography: a systematic survey
Tarun Agrawal, Prakash Choudhary. The Visual Computer, 2022. Cites: paper

Attention based automated radiology report generation using CNN and LSTM
Mehreen Sirshar, Muhammad Faheem Khalil Paracha, Muhammad Usman Akram et al. PLoS ONE, 2022. Cites: paper

The Subadult Virtual Anthropology Database (SVAD): An Accessible Repository of Contemporary Subadult Reference Data
Kyra E. Stull, Louise Corron. Forensic Sciences, 2022. Cites: paper

A Critical Analysis Of Nlp and Clinical Correctness Metrics to Measure Progress on X-Ray Report Generation
Pablo Pino, Denis Parra, Jocelyn Dunstan et al. SSRN Electronic Journal, 2022. Cites: paper

An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
Huy‐Hieu Pham, Ha Q. Nguyen, Khanh Lam et al. IEEE Access, 2022. Cites: paper

An Inclusive Task-Aware Framework for Radiology Report Generation
Lin Wang, Munan Ning, Donghuan Lu et al. Lecture notes in computer science, 2022. Cites: paper

Application of Federated Learning in Medical Imaging
Ehsan Degan, Shafiq Abedin, David Beymer et al. Springer eBooks, 2022. Cites: dataset, paper

A Review of Medical Federated Learning: Applications in Oncology and Cancer Research
Alexander Chowdhury, Hasan Kassem, Nicolas Padoy et al. Lecture notes in computer science, 2022. Cites: paper

Artificial Intelligence-Based Identification of Normal Chest Radiographs: A Simulation Study in a Multicenter Health Screening Cohort
Hyunsuk Yoo, Eun Young Kim, Hyungjin Kim et al. Korean Journal of Radiology, 2022. Cites: paper

Artificial intelligence: opportunities in lung cancer.
Kai Zhang, Kezhong Chen. PubMed, 2022. Cites: paper

A Survey on Attention Mechanisms for Medical Applications: are we Moving Toward Better Algorithms?
Tiago Gonçalves, Isabel Rio-Torto, Luís Filipe Teixeira et al. IEEE Access, 2022. Cites: paper

Automated Radiology Report Generation Using a Transformer-Template System: Improved Clinical Accuracy and an Assessment of Clinical Safety
Brandon Abela, Jumana Abu-Khalaf, Chi-Wei Robin Yang et al. Lecture notes in computer science, 2022. Cites: paper

Benchmarking and Boosting Transformers for Medical Image Classification
DongAo Ma, Mohammad Reza Hosseinzadeh Taher, Jiaxuan Pang et al. Lecture notes in computer science, 2022. Cites: paper

BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis
Masoud Monajatipoor, Mozhdeh Rouhsedaghat, Liunian Harold Li et al. Lecture notes in computer science, 2022. Cites: paper

BioSimCSE: BioMedical Sentence Embeddings using Contrastive learning
Kamal raj Kanakarajan, Bhuvana Kundumani, Abhijith Neil Abraham et al. International Workshop on Health Text Mining and Information Analysis (LOUHI), 2022. Cites: paper

Breaking with Fixed Set Pathology Recognition Through Report-Guided Contrastive Training
Constantin Seibold, Simon Reiß, Muhammad Saquib Sarfraz et al. Lecture notes in computer science, 2022. Cites: paper

CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships Between Chest X-Rays
Gaurang Karwande, Amarachi Blessing Mbakwe, Joy Tzung-Yu Wu et al. Lecture notes in computer science, 2022. Cites: paper

Cross-Modal Prototype Driven Network for Radiology Report Generation
Jun Wang, Abhir H. Bhalerao, Yulan He. Lecture notes in computer science, 2022. Cites: paper

Demographic Reporting in Publicly Available Chest Radiograph Data Sets: Opportunities for Mitigating Sex and Racial Disparities in Deep Learning Models
Paul Hyunsoo Yi, Tae Kyung Kim, Eliot L. Siegel et al. Journal of the American College of Radiology, 2022. Cites: paper

Detection of Pneumothorax from Chest X-Ray Data Using Machine Learning: A Comprehensive Survey
Arpan Garg, Bobbinpreet Kaur. Communications in computer and information science, 2022. Cites: paper

Diagnostic effect of artificial intelligence solution for referable thoracic abnormalities on chest radiography: a multicenter respiratory outpatient diagnostic cohort study
Kwang Nam Jin, Eun Young Kim, Young Jae Kim et al. European Radiology, 2022. Cites: paper

Few-Shot Learning Geometric Ensemble for Multi-label Classification of Chest X-Rays
Dana Moukheiber, Saurabh Mahindre, Lama Moukheiber et al. Lecture notes in computer science, 2022. Cites: paper

GazeRadar: A Gaze and Radiomics-Guided Disease Localization Framework
Moinak Bhattacharya, Shubham Jain, Prateek Prasanna. Lecture notes in computer science, 2022. Cites: paper

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