Publications citing MIMIC-CXR Database v2.1.0

Opportunities and challenges for ChatGPT and large language models in biomedicine and health
Shubo Tian, Qiao Jin, Lana E Yeganova et al. Briefings in Bioinformatics, 2023. Cites: paper

Using Deep Learning and Adaptive Window Adjustment to Facilitate the Detection of Pulmonary Edema Detection in Chest X-Rays
Yen‐Jung Chiu, Chao-Chun Chuang, Shih-Tsang Tang. International Conference on Digital Medicine and Image Processing (DMIP), 2023. Cites: dataset

Derivation and Validation of a Machine Learning Approach to Detect and Mitigate Biases in Healthcare Data
Faris F. Gulamali, Ashwin Shreekant Sawant, Lora E. Liharska et al. medRxiv, 2023. Cites: paper

Detecting and Processing Unsuspected Sensitive Variables for Robust Machine Learning
Laurent Risser, Agustin Martin Picard, Lucas Hervier et al. Algorithms, 2023. Cites: paper

Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology
Sang Joon Park, Eun Sun Lee, Kyung Sook Shin et al. Medical Image Analysis, 2023. Cites: paper

Attention Enhanced Network with Semantic Inspector for Medical Image Report Generation
Yihan Lin, Qian Jun Tang, Hao Wang et al. IEEE International Conference on Tools with Artificial Intelligence (ICTAI), 2023. Cites: paper

A New Model of Organizing Mass Screening Based on Stand-Alone Artificial Intelligence Used for Fluorography Image Triage
Yuriy Aleksandrovich Vasilev, Anton V. Vladzymyrskyy, Kirill M. Arzamasov et al. ЗДОРОВЬЕ НАСЕЛЕНИЯ И СРЕДА ОБИТАНИЯ - ЗНиСО / PUBLIC HEALTH AND LIFE ENVIRONMENT, 2023. Cites: paper

Coarse Race and Ethnicity Labels Mask Granular Underdiagnosis Disparities in Deep Learning Models for Chest Radiograph Diagnosis
Preetham Bachina, Sean P. Garin, Pranav Kulkarni et al. Radiology, 2023. Cites: paper

R2GenGPT: Radiology Report Generation with frozen LLMs
Zhanyu Wang, Lingqiao Liu, Lei Wang et al. Meta-Radiology, 2023. Cites: paper

Artificial General Intelligence (AGI) for Medical Education and Training
Kennedy g Lema. 2023. Cites: paper

RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training
Zheng Peng Yuan, Qiao Jin, Chuanqi Tan et al. ACM International Conference on Multimedia (ACM MM), 2023. Cites: paper

Genetic Convolutional Neural Networks Approach for Disease Detection From Chest X-Ray Images
Amina Djoudi, Ahmed Amine Zaid, Younes Guellouma et al. International Conference on Pattern Analysis and Intelligent Systems (PAIS), 2023. Cites: paper

Machine Learning Empowering Personalized Medicine: A Comprehensive Review of Medical Image Analysis Methods
Irena Galić, Marija Habijan, Hrvoje Leventić et al. Electronics, 2023. Cites: paper

Quality indicators in endoscopic screening and the role of artificial intelligence
Takeshi Okamoto, Toshiaki Hirasawa. Digestive Endoscopy, 2023. Cites: paper

Multi-Task Paired Masking With Alignment Modeling for Medical Vision-Language Pre-Training
Ke Zhang, Yan Qin Yang, Jun Yu et al. IEEE Transactions on Multimedia, 2023. Cites: paper

EfficienTransNet: An Automated Chest X-ray Report Generation Paradigm
Chayan Mondal, Duc-Son Pham, Ashu Gupta et al. International Workshop on Multimodal and Responsible Affective Computing (MRAC), 2023. Cites: paper

Joint classification and segmentation for an interpretable diagnosis of acute respiratory distress syndrome from chest x-rays
Mohammad Yahyatabar, Philippe A. Jouvet, Farida Cheriet A. Journal of medical imaging, 2023. Cites: paper

Fact-Checking of AI-Generated Reports
Razi Mahmood, Ge Wang, Mannudeep K. Kalra et al. Lecture notes in computer science, 2023. Cites: paper

Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting
Francesco Dalla Serra, Chaoyang Wang, Fani Deligianni et al. Lecture notes in computer science, 2023. Cites: paper

Tailoring Large Language Models to Radiology: A Preliminary Approach to LLM Adaptation for a Highly Specialized Domain
Zhengliang Liu, Aoxiao Zhong, Yiwei Li et al. Lecture notes in computer science, 2023. Cites: paper

On the challenges and perspectives of foundation models for medical image analysis
Shaoting Zhang, Dimitris Metaxas. Medical Image Analysis, 2023. Cites: paper

Improving model fairness in image-based computer-aided diagnosis
Mingquan Lin, Tianhao Li, Yifan Yang et al. Nature Communications, 2023. Cites: paper

An Empirical Analysis for Zero-Shot Multi-Label Classification on COVID-19 CT Scans and Uncurated Reports
Ethan Dack, Lorenzo Brigato, Matthew McMurray et al. IEEE International Conference on Computer Vision Workshops, 2023. Cites: paper

An Optimized Ensemble Framework for Multi-Label Classification on Long-Tailed Chest X-ray Data
Jaehyup Jeong, Bo-Soung Jeoun, Yeonju Park et al. IEEE International Conference on Computer Vision Workshops, 2023. Cites: paper

Chest X-Ray Feature Pyramid Sum Model with Diseased Area Data Augmentation Method
Chang-Hyun Kim, Giyeol Kim, Sooyoung Yang et al. IEEE International Conference on Computer Vision Workshops, 2023. Cites: paper

CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification
Dongkyun Kim. IEEE International Conference on Computer Vision Workshops, 2023. Cites: paper

Multimodal Contrastive Learning and Tabular Attention for Automated Alzheimer’s Disease Prediction
Weichen Huang. IEEE International Conference on Computer Vision Workshops, 2023. Cites: paper

Feasibility and Prospect of Privacy-preserving Large Language Models in Radiology
Wenli Cai. Radiology, 2023. Cites: paper

Feasibility of Using the Privacy-preserving Large Language Model Vicuna for Labeling Radiology Reports
Pritam Mukherjee, Benjamin Hou, Ricardo Bigolin Lanfredi et al. Radiology, 2023. Cites: paper

Foreground-Background Separation through Concept Distillation from Generative Image Foundation Models
Mischa Dombrowski, Hadrien Reynaud, Matthew Baugh et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

Instrumental Variable Learning for Chest X-ray Classification
Weizhi Nie, Chen Zhang, Dan Song et al. Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics, 2023. Cites: paper

LIMITR: Leveraging Local Information for Medical Image-Text Representation
Gefen Dawidowicz, Elad Hirsch, Ayellet Tal. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

MedKLIP: Medical Knowledge Enhanced Language-Image Pre-Training for X-ray Diagnosis
Chaoyi Wu, Xiaoman Zhang, Ya Zhang et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: dataset

Partition-and-Debias: Agnostic Biases Mitigation via A Mixture of Biases-Specific Experts
Jiaxuan Li, Duc Minh Vo, Hideki Nakayama. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

PRIOR: Prototype Representation Joint Learning from Medical Images and Reports
Pujin Cheng, Li Lin, Junyan Lyu et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

The stochastic digital human is now enrolling for in silico imaging trials—methods and tools for generating digital cohorts
Aldo G. Badano, Miguel A. Lago, Elena Sizikova et al. Progress in Biomedical Engineering, 2023. Cites: paper

Towards Unifying Medical Vision-and-Language Pre-training via Soft Prompts
Zhihong Chen, Shizhe Diao, Benyou Wang et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

Unify, Align and Refine: Multi-Level Semantic Alignment for Radiology Report Generation
Yaowei Li, Bang Yang, Xuxin Cheng et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data
Maya Varma, Jean-Benoit Delbrouck, Sarah Hooper et al. IEEE/CVF International Conference on Computer Vision (ICCV), 2023. Cites: paper

Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis
Kai Ma, Siyuan He, Grant Sinha et al. Sensors, 2023. Cites: paper

Explainable Deep Learning Methods in Medical Image Classification: A Survey
Cristiano Patrício, João C. Neves, Luís Filipe Teixeira. ACM Computing Surveys, 2023. Cites: paper

MDF-Net for abnormality detection by fusing X-rays with clinical data
Chihcheng Hsieh, Isabel Blanco Nobre, Sandra Costa Sousa et al. Scientific Reports, 2023. Cites: dataset, paper

Patient Reidentification from Chest Radiographs: An Interpretable Deep Metric Learning Approach and Its Applications
Matthew MacPherson, Charles E. Hutchinson, Carolyn Horst et al. Radiology Artificial Intelligence, 2023. Cites: paper

Towards Generalist Foundation Model for Radiology
Weidi Xie, Chaoyi Wu, Xiaoman Zhang et al. Research Square, 2023. Cites: paper

Advancements in Standardizing Radiological Reports: A Comprehensive Review
Filippo Pesapane, Priyan Maleuwe Tantrige, P. De Marco et al. Medicina, 2023. Cites: paper

A Systematic Literature Review of Deep Learning Application in Multiclass Anomaly Detection for Chest Medical Imaging
Philips, Bens Pardamean, Gregorius Natanael Elwirehardja et al. International Conference of Computer and Informatics Engineering (IC2IE), 2023. Cites: paper

LT-ViT: A Vision Transformer for Multi-Label Chest X-Ray Classification
Umar Marikkar, Sara Atito, Muhammad Awais et al. Proceedings - International Conference on Image Processing, 2023. Cites: paper

MKCL: Medical Knowledge with Contrastive Learning model for radiology report generation
Xiaodi Hou, Zhi Liu, Xiaobo Li et al. Journal of Biomedical Informatics, 2023. Cites: paper

Self Adaptive Global-Local Feature Enhancement for Radiology Report Generation
Yuhao Wang, Kai Wang, Xiaohong Liu et al. Proceedings - International Conference on Image Processing, 2023. Cites: paper

A Real-world Dataset and Benchmark For Foundation Model Adaptation in Medical Image Classification
Dequan Wang, Xiaosong Wang, Lilong Wang et al. Scientific Data, 2023. Cites: paper

Cited by