ArticleScientific data2021
Creation and validation of a chest X-ray dataset with eye-tracking and report dictation for AI development.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Systemic fragility in European total intravenous anesthesia delivery and opportunities for resilient real-time decision support.Communications medicine · 2026Review
- [Visual prior-guided masked image modeling enhances chest X-ray diagnostic efficacy].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- RadGazeGen: radiomics and gaze-guided chest X-ray generation using diffusion models.Journal of medical imaging (Bellingham, Wash.) · 2026Article
- Standardizing DICOM annotation: deep learning enhances body part description in X-ray image retrieval for clinical research.BMC medical imaging · 2025Article
- Eye Tracking-Enhanced Deep Learning for Medical Image Analysis: A Systematic Review on Data Efficiency, Interpretability, and Multimodal Integration.Bioengineering (Basel, Switzerland) · 2025Review
- Joint enhancement of automatic chest x-ray diagnosis and radiological gaze prediction with multistage cooperative learning.Medical physics · 2025Article
- Diagnosis and Treatment of Primary Tracheobronchial Tumors.Cancer medicine · 2025Review
- Modeling radiologists' cognitive processes using a digital gaze twin to enhance radiology training.Scientific reports · 2025Article
- Multimodal contrastive learning for enhanced explainability in pediatric brain tumor molecular diagnosis.Scientific reports · 2025Article
- ItpCtrl-AI: End-to-end interpretable and controllable artificial intelligence by modeling radiologists' intentions.Artificial intelligence in medicine · 2025Article
- Discrimination of Radiologists' Experience Level Using Eye-Tracking Technology and Machine Learning: Case Study.JMIR formative research · 2025Article
- Enhancing colorectal polyp classification using gaze-based attention networks.PeerJ. Computer science · 2025Article
- Bridging human and machine intelligence: Reverse-engineering radiologist intentions for clinical trust and adoption.Computational and structural biotechnology journal · 2024Article
- The Use of Machine Learning in Eye Tracking Studies in Medical Imaging: A Review.IEEE journal of biomedical and health informatics · 2024Review
- DECODING RADIOLOGISTS' INTENTIONS: A NOVEL SYSTEM FOR ACCURATE REGION IDENTIFICATION IN CHEST X-RAY IMAGE ANALYSIS.Proceedings. IEEE International Symposium on Biomedical Imaging · 2024Article
- From explanation to intervention: Interactive knowledge extraction from Convolutional Neural Networks used in radiology.PloS one · 2024Article
- Effects of tracker location on the accuracy and precision of the Gazepoint GP3 HD for spectacle wearers.Behavior research methods · 2024Article
- Effective processing pipeline PACE 2.0 for enhancing chest x-ray contrast and diagnostic interpretability.Scientific reports · 2023Article
- Visual Image Annotation for Bowel Obstruction: Repeatability and Agreement with Manual Annotation and Neural Networks.Journal of digital imaging · 2023Article
- A Review of Recent Advances in Deep Learning Models for Chest Disease Detection Using Radiography.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We developed a rich dataset of Chest X-Ray (CXR) images to assist investigators in artificial intelligence. The data were collected using an eye-tracking system while a radiologist reviewed and reported on 1,083 CXR images. The dataset contains the following aligned data: CXR image, transcribed radiology report text, radiologist's dictation audio and eye gaze coordinates data. We hope this dataset can contribute to various areas of research particularly towards explainable and multimodal deep learning/machine learning methods. Furthermore, investigators in disease classification and localization, automated radiology report generation, and human-machine interaction can benefit from these data. We report deep learning experiments that utilize the attention maps produced by the eye gaze dataset to show the potential utility of this dataset.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.