Artificial intelligence literacy: developing a multi-institutional infrastructure for AI education

JD Perchik, AD Smith, AA Elkassem, JM Park… - Academic radiology, 2023 - Elsevier
Rationale and Objectives To evaluate the effectiveness of an artificial intelligence (AI) in
radiology literacy course on participants from nine radiology residency programs in the …

Quantitative imaging decision support (QIDSTM) tool consistency evaluation and radiomic analysis by means of 594 metrics in lung carcinoma on chest CT scan

R Fusco, V Granata, MA Mazzei, N Di Meglio… - Cancer …, 2021 - journals.sagepub.com
Objective: To evaluate the consistency of the quantitative imaging decision support
(QIDSTM) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan …

A blockchain-based protocol for tracking user access to shared medical imaging

EJ De Aguiar, AJ Dos Santos, RI Meneguette… - Future Generation …, 2022 - Elsevier
Modern healthcare systems are complex and regularly share sensitive data among multiple
stakeholders, such as doctors, patients, and pharmacists. Patients' data has increased and …

Convolutional neural network model based on radiological images to support COVID-19 diagnosis: Evaluating database biases

CBS Maior, JMM Santana, ID Lins, MJC Moura - Plos one, 2021 - journals.plos.org
As SARS-CoV-2 has spread quickly throughout the world, the scientific community has spent
major efforts on better understanding the characteristics of the virus and possible means to …

Quantitative molecular positron emission tomography imaging using advanced deep learning techniques

H Zaidi, I El Naqa - Annual review of biomedical engineering, 2021 - annualreviews.org
The widespread availability of high-performance computing and the popularity of artificial
intelligence (AI) with machine learning and deep learning (ML/DL) algorithms at the helm …

[HTML][HTML] Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method

OF Ahmad, Y Mori, M Misawa, S Kudo… - …, 2021 - thieme-connect.com
Background Artificial intelligence (AI) research in colonoscopy is progressing rapidly but
widespread clinical implementation is not yet a reality. We aimed to identify the top …

REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays

R Bigolin Lanfredi, M Zhang, WF Auffermann, J Chan… - Scientific data, 2022 - nature.com
Deep learning has shown recent success in classifying anomalies in chest x-rays, but
datasets are still small compared to natural image datasets. Supervision of abnormality …

A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations

A Agrawal, GD Khatri, B Khurana, AD Sodickson… - Emergency …, 2023 - Springer
Purpose There is a growing body of diagnostic performance studies for emergency
radiology-related artificial intelligence/machine learning (AI/ML) tools; however, little is …

Accounting for data variability in multi-institutional distributed deep learning for medical imaging

N Balachandar, K Chang… - Journal of the …, 2020 - academic.oup.com
Objectives Sharing patient data across institutions to train generalizable deep learning
models is challenging due to regulatory and technical hurdles. Distributed learning, where …

Artificial intelligence CAD tools in trauma imaging: a scoping review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel

D Dreizin, PV Staziaki, GD Khatri, NM Beckmann… - Emergency …, 2023 - Springer
Abstract Background AI/ML CAD tools can potentially improve outcomes in the high-stakes,
high-volume model of trauma radiology. No prior scoping review has been undertaken to …