Eye Gaze Data for Chest X-rays

We created a rich multimodal dataset for the Chest X-Ray (CXR) domain. The data was 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. We hope this dataset can contribute to various fields of research with applications in machine learning such as deep learning explainability, multi-modal fusion, disease classification, and automated radiology report generation to name a few. The images were selected from the MIMIC-CXR Database and were associated with studies from 1,038 subjects (female: 495, male: 543) who had age range 20 - 80 years old.