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Database Credentialed Access

EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images

Seongsu Bae, Daeun Kyung, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei JI, Eric Chang, Tackeun Kim, Edward Choi

We present EHRXQA, the first multi-modal EHR QA dataset combining structured patient records with aligned chest X-ray images. EHRXQA contains a comprehensive set of QA pairs covering image-related, table-related, and image+table-related questions.

question answering machine learning evaluation visual question answering electronic health records benchmark multi-modal question answering deep learning chest x-ray ehr question answering semantic parsing

Published: July 23, 2024. Version: 1.0.0

Database Credentialed Access

MS-CXR: Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing

Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel Coelho de Castro, Anton Schwaighofer, Stephanie Hyland, Maria Teodora Wetscherek, Tristan Naumann, Aditya Nori, Javier Alvarez Valle, Hoifung Poon, Ozan Oktay

MS-CXR is a new dataset containing 1162 Chest X-ray bounding box labels paired with radiology text descriptions, annotated and verified by two board-certified radiologists.

vision-language processing chest x-ray

Published: May 16, 2022. Version: 0.1

Database Credentialed Access

Medical-Diff-VQA: A Large-Scale Medical Dataset for Difference Visual Question Answering on Chest X-Ray Images

Xinyue Hu, Lin Gu, Qiyuan An, Mengliang Zhang, liangchen liu, Kazuma Kobayashi, Tatsuya Harada, Ronald Summers, Yingying Zhu

MIMIC-Diff-VQA provides a large-scale dataset for Difference visual question answering in medical chest x-ray images.

difference vqa vqa difference visual question answering visual question answering chest x-ray

Published: Sept. 15, 2023. Version: 1.0.0

Database Credentialed Access

Radiology Report Expert Evaluation (ReXVal) Dataset

Feiyang Yu, Mark Endo, Rayan Krishnan, Ian Pan, Andy Tsai, Eduardo Pontes Reis, Eduardo Kaiser Ururahy Nunes Fonseca, Henrique Lee, Zahra Shakeri, Andrew Ng, Curtis Langlotz, Vasantha Kumar Venugopal, Pranav Rajpurkar

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports.

Published: June 20, 2023. Version: 1.0.0

Database Restricted Access

REFLACX: Reports and eye-tracking data for localization of abnormalities in chest x-rays

Ricardo Bigolin Lanfredi, Mingyuan Zhang, William Auffermann, Jessica Chan, Phuong-Anh Duong, Vivek Srikumar, Trafton Drew, Joyce Schroeder, Tolga Tasdizen

This dataset contains 3032 cases of eye-tracking data collected while five radiologists dictated reports for frontal chest x-rays, synchronized timestamped dictation transcription, and manual labels for validation of localization of abnormalities.

eye tracking radiology report reflacx fixations computer vision chest x-rays gaze radiology machine learning deep learning

Published: Sept. 27, 2021. Version: 1.0.0

Database Credentialed Access

RadNLI: A natural language inference dataset for the radiology domain

Yasuhide Miura, Yuhao Zhang, Emily Tsai, Curtis Langlotz, Dan Jurafsky

A radiology NLI dataset introduced in the paper: Improving Factual Completeness and Consistency of Image-to-text Radiology Report Generation

Published: June 29, 2021. Version: 1.0.0

Database Credentialed Access

Eye Gaze Data for Chest X-rays

Alexandros Karargyris, Satyananda Kashyap, Ismini Lourentzou, Joy Wu, Matthew Tong, Arjun Sharma, Shafiq Abedin, David Beymer, Vandana Mukherjee, Elizabeth Krupinski, Mehdi Moradi

This dataset was a collected using an eye tracking system while a radiologist interpreted and read 1,083 public CXR images. The dataset contains the following aligned modalities: image, transcribed report text, dictation audio and eye gaze data.

audio convolutional network heatmap eye tracking explainability chest cxr multimodal radiology machine learning deep learning chest x-ray

Published: Sept. 12, 2020. Version: 1.0.0

Database Credentialed Access

Chest ImaGenome Dataset

Joy Wu, Nkechinyere Agu, Ismini Lourentzou, Arjun Sharma, Joseph Paguio, Jasper Seth Yao, Edward Christopher Dee, William Mitchell, Satyananda Kashyap, Andrea Giovannini, Leo Anthony Celi, Tanveer Syeda-Mahmood, Mehdi Moradi

The Chest ImaGenome dataset is a scene graph dataset with additional chronological comparison relations for chest X-rays. It is automatically derived from the MIMIC-CXR dataset. A manually annotated gold standard is also available for 500 patients.

scene graph visual dialogue object detection semantic reasoning bounding box relation extraction knowledge graph explainability reasoning chest cxr disease progression multimodal radiology machine learning visual question answering deep learning chest x-ray

Published: July 13, 2021. Version: 1.0.0

Database Credentialed Access

Generalized Image Embeddings for the MIMIC Chest X-Ray dataset

Andrew Sellergren, Atilla Kiraly, Tom Pollard, Wei-Hung Weng, Yun Liu, Akib Uddin, Christina Chen

This database contains compact information-rich embeddings of the MIMIC-CXR Database v2.0.0 using the CXR Foundation API v1.0.

Published: Feb. 22, 2023. Version: 1.0