Publications by authors named "Jarrel Seah"

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Why 2D Matters: Comparative Evaluation of 2D and 3D T1-Weighted Imaging of the Skull Base and Neck.
Amy F Juliano, Nathan Huey, Laura V Romo, Hillary R Kelly, Manuel Patino, Jarrel Seah

AJNR Am J Neuroradiol· November 2025

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Are Deep White Matter Hyperintensities Associated with Amyloid-Related Imaging Abnormalities in Patients with Alzheimer Disease Treated with Lecanemab?
Saurabh Rohatgi, Shenghua Zhu, Esteban Calle Cadavid, Jeremy N Ford, Benjamin M Kozak, Jarrel C Seah

AJNR Am J Neuroradiol· November 2025

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Enhancing Radiographic Diagnosis: CycleGAN-Based Methods for Reducing Cast Shadow Artifacts in Wrist Radiographs.
Stanley A Norris, Daniel Carrion, Michael Ditchfield, Manuel Gubser, Jarrel Seah

J Imaging Inform Med· October 2025

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Drafting the Future: The Dawn of AI Report Generation in Radiology.
Jarrel C Y Seah, Jennifer S N Tang, Aengus Tran

Radiology· July 2025

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Applications and potential of machine, learning augmented chest X-ray interpretation in cardiology.
Michael R Milne, Hassan K Ahmad, Quinlan D Buchlak, Nazanin Esmaili, Cyril Tang, Jarrel Seah

Minerva Cardiol Angiol· February 2025

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Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations.
Joseph E Alderman, Joanne Palmer, Elinor Laws, Melissa D McCradden, Johan Ordish, Jarrel Seah

Lancet Digit Health· January 2025

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Generative Large Language Models for Detection of Speech Recognition Errors in Radiology Reports.
Reuben A Schmidt, Jarrel C Y Seah, Ke Cao, Lincoln Lim, Wei Lim

Radiol Artif Intell· March 2024

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Effects of a comprehensive brain computed tomography deep learning model on radiologist detection accuracy.
Quinlan D Buchlak, Cyril H M Tang, Jarrel C Y Seah, Andrew Johnson, Xavier Holt

Eur Radiol· February 2024

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Analysis of Line and Tube Detection Performance of a Chest X-ray Deep Learning Model to Evaluate Hidden Stratification.
Cyril H M Tang, Jarrel C Y Seah, Hassan K Ahmad, Michael R Milne, Jeffrey B Wardman

Diagnostics (Basel)· July 2023

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Machine Learning Augmented Interpretation of Chest X-rays: A Systematic Review.
Hassan K Ahmad, Michael R Milne, Quinlan D Buchlak, Nalan Ektas, Georgina Sanderson, Jarrel C Y Seah

Diagnostics (Basel)· February 2023

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Evaluation of an Artificial Intelligence Model for Detection of Pneumothorax and Tension Pneumothorax in Chest Radiographs.
James M Hillis, Bernardo C Bizzo, Sarah Mercaldo, John K Chin, Isabella Newbury-Chaet, Jarrel C Y Seah

JAMA Netw Open· December 2022

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Pathophysiological Mechanisms of Gastro-esophageal Reflux After Sleeve Gastrectomy.
Yazmin Johari, Gillian Lim, Anagi Wickremasinghe, Helen Yue, Jarrel Seah

Ann Surg· November 2022

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Retrospective analysis and prospective validation of an AI-based software for intracranial haemorrhage detection at a high-volume trauma centre.
Adil Zia, Calvin Fletcher, Shalini Bigwood, Prasanna Ratnakanthan, Jarrel Seah

Sci Rep· November 2022

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Diagnostic accuracy of a commercially available deep-learning algorithm in supine chest radiographs following trauma.
Jacob Gipson, Victor Tang, Jarrel Seah, Helen Kavnoudias, Adil Zia

Br J Radiol· June 2022

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Machine learning approaches for imaging-based prognostication of the outcome of surgery for mesial temporal lobe epilepsy.
Benjamin Sinclair, Varduhi Cahill, Jarrel Seah, Andy Kitchen, Lucy E Vivash

Epilepsia· May 2022

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Charting the potential of brain computed tomography deep learning systems.
Quinlan D Buchlak, Michael R Milne, Jarrel Seah, Andrew Johnson, Gihan Samarasinghe

J Clin Neurosci· May 2022

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Prime Time for Artificial Intelligence in Interventional Radiology.
Jarrel Seah, Tom Boeken, Marc Sapoval, Gerard S Goh

Cardiovasc Intervent Radiol· March 2022

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Do comprehensive deep learning algorithms suffer from hidden stratification? A retrospective study on pneumothorax detection in chest radiography.
Jarrel Seah, Cyril Tang, Quinlan D Buchlak, Michael Robert Milne, Xavier Holt

BMJ Open· December 2021

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Assessment of the effect of a comprehensive chest radiograph deep learning model on radiologist reports and patient outcomes: a real-world observational study.
Catherine M Jones, Luke Danaher, Michael R Milne, Cyril Tang, Jarrel Seah

BMJ Open· December 2021

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Artificial intelligence in medical imaging: implications for patient radiation safety.
Jarrel Seah, Zoe Brady, Kyle Ewert, Meng Law

Br J Radiol· October 2021

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CLiP, catheter and line position dataset.
Jennifer S N Tang, Jarrel C Y Seah, Adil Zia, Jay Gajera, Richard N Schlegel

Sci Data· October 2021

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Chest radiographs and machine learning - Past, present and future.
Catherine M Jones, Quinlan D Buchlak, Luke Oakden-Rayner, Michael Milne, Jarrel Seah

J Med Imaging Radiat Oncol· August 2021

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Effect of a comprehensive deep-learning model on the accuracy of chest x-ray interpretation by radiologists: a retrospective, multireader multicase study.
Jarrel C Y Seah, Cyril H M Tang, Quinlan D Buchlak, Xavier G Holt, Jeffrey B Wardman

Lancet Digit Health· August 2021

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Artificial intelligence and medical imaging: applications, challenges and solutions.
Meng Law, Jarrel Seah, George Shih

Med J Aust· June 2021

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Delayed intracranial hemorrhage after trauma.
Biswadev Mitra, Tomi Ruggles, Jarrel Seah, Charne Miller, Mark C Fitzgerald

Brain Inj· March 2021

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