Resources


Database Open Access

Integration of Electroencephalogram and Eye-Gaze Datasets for Performance Evaluation in Fundamentals of Laparoscopic Surgery (FLS) Tasks

Somayeh B Shafiei, Saeed Shadpour

Brain activity and eye gaze data were collected from a group of 25 participants who completed the FLS tasks using a trainer box (Pyxus®). Each participant performed the tasks five times, and their performance was evaluated by an expert rater.

Published: Aug. 23, 2023. Version: 1.0.0

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Database Open Access

Electroencephalogram and eye-gaze datasets for robot-assisted surgery performance evaluation

Somayeh B Shafiei, Saeed Shadpour, James Mohler, Mehdi Seilanian Toussi, Philippa Doherty, Zhe Jing

The brain activity and eye gaze data were recorded from 25 participants performing surgical tasks using a robot simulator. The performance score was created by the simulator. Data can be used to evaluate surgical performance.

Published: July 14, 2023. Version: 1.0.0

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Database Restricted Access

MIMIC-Eye: Integrating MIMIC Datasets with REFLACX and Eye Gaze for Multimodal Deep Learning Applications

Chihcheng Hsieh, Chun Ouyang, Jacinto C Nascimento, Joao Pereira, Joaquim Jorge, Catarina Moreira

MIMIC-Eye: Integrating MIMIC Datasets with REFLACX and Eye Gaze for Multimodal Deep Learning Applications

Published: March 23, 2023. 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 multimodal chest x-ray machine learning radiology explainability chest cxr deep learning

Published: Sept. 12, 2020. Version: 1.0.0


Database Open Access

Eye Tracking Dataset for the 12-Lead Electrocardiogram Interpretation of Medical Practitioners and Students

Mohammed Tahri Sqalli, Dena Al-Thani, Mohamed Elshazly, Mohammed Al-Hijji

The project aims at collecting a dataset using eye-tracking technology to understand the 12-lead electrocardiogram interpretation visual behavior for medical practitioners and students with different expertise levels.

human vision medical students ecg interpretation medical image interpretation medical practice medical education human-computer interaction eye-tracking medical practitioners visual expertise electrocardiogram ecg

Published: March 16, 2022. 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.

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

Published: Sept. 27, 2021. 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.

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

Published: Sept. 27, 2021. Version: 1.0.0