John T Mongan

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Automated detection of IVC filters on radiographs with deep convolutional neural networks

J. Mongan, M. Kohli, R. Houshyar, 2022, Abdominal Radiology.

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification pdf

Christos Davatzikos, Russell T. Shinohara, Spyridon Bakas, 2021, ArXiv.

The radiologist's workflow environment: evaluation of disruptors and potential implications.

Akash P Kansagra, John Mongan, J. Mongan, 2014, Journal of the American College of Radiology : JACR.

Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge.

L. Shah, Robyn L. Ball, S. Halabi, 2020, Radiology. Artificial intelligence.

Limitations of atom-centered dielectric functions in implicit solvent models.

J Andrew McCammon, Jessica M J Swanson, John Mongan, 2005, The journal of physical chemistry. B.

Constant pH molecular dynamics in generalized Born implicit solvent

D. Case, J. Mongan, J. Mccammon, 2004, J. Comput. Chem..

Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers.

J. Mongan, C. E. Kahn, L. Moy, 2020, Radiology. Artificial intelligence.

Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules.

J. Mongan, J. Mccammon, D. Hamelberg, 2004, The Journal of chemical physics.

Effect of shelter-in-place on emergency department radiology volumes during the COVID-19 pandemic

Paul M. Murphy, J. Mongan, M. Kohli, 2020, Emergency Radiology.

Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study

J. Mongan, Andrew G. Taylor, Clinton Mielke, 2018, PLoS medicine.

Interactive essential dynamics

John Mongan, J. Mongan, John T Mongan, 2004, J. Comput. Aided Mol. Des..

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Maria A. Zuluaga, M. Jorge Cardoso, Suyash P. Awate, 2023, ArXiv.

Generalized Born model with a simple, robust molecular volume correction.

J Andrew McCammon, Carlos Simmerling, John Mongan, 2007, Journal of chemical theory and computation.

Pancreatic imaging mimics: part 1, imaging mimics of pancreatic adenocarcinoma.

J. Mongan, F. Coakley, A. Qayyum, 2012, AJR. American journal of roentgenology.

Contrast Enhanced Ultrasound as a Radiation‐Free Alternative to Fluoroscopic Nephrostogram for Evaluating Ureteral Patency

J. Mongan, M. Stoller, S. Weinstein, 2017, The Journal of urology.

The RSNA International COVID-19 Open Radiology Database (RICORD)

M. Lungren, J. Mongan, B. Erickson, 2021, Radiology.

Analysis of integral expressions for effective Born radii.

John Mongan, Alexey Onufriev, J. Mongan, 2007, The Journal of chemical physics.

Automated coronary calcium scoring using deep learning with multicenter external validation

Ross W. Filice, P. Rajpurkar, M. Budoff, 2021, npj Digital Medicine.

Potent, selective pyrone-based inhibitors of stromelysin-1.

J Andrew McCammon, John Mongan, Seth M Cohen, 2005, Journal of the American Chemical Society.

Biomolecular simulations at constant pH.

John Mongan, David A Case, D. Case, 2005, Current opinion in structural biology.

High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks

Michael Blum, Alvin Rajkomar, John Mongan, 2016, Journal of Digital Imaging.

Age and sex-dependent trends in pulmonary embolism testing and derivation of a clinical decision rule for young patients

J. Kline, R. Smith-Bindman, John T Mongan, 2015, Emergency Medicine Journal.

The RSNA Pulmonary Embolism CT Dataset.

Robyn L. Ball, S. Halabi, M. Lungren, 2021, Radiology. Artificial intelligence.

How far have we come? Artificial intelligence for chest radiograph interpretation.

K. Kallianos, J. Mongan, S. Antani, 2019, Clinical radiology.

The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs

Katherine P. Andriole, T. Cook, P. Lakhani, 2021, Journal of Digital Imaging.

Beyond Prostate Adenocarcinoma: Expanding the Differential Diagnosis in Prostate Pathologic Conditions.

J. Mongan, S. Behr, J. Simko, 2016, Radiographics : a review publication of the Radiological Society of North America, Inc.

Feasibility of Antegrade Contrast-enhanced US Nephrostograms to Evaluate Ureteral Patency.

J. Mongan, R. Goldstein, M. Stoller, 2017, Radiology.

Feasibility of Retrograde Ureteral Contrast Injection to Guide Ultrasonographic Percutaneous Renal Access in the Nondilated Collecting System.

J. Mongan, S. Weinstein, T. Chi, 2017, Journal of endourology.

What Physicians and Health Organizations Should Know About Mandated Imaging Appropriate Use Criteria

Ramin Khorasani, Pamela Johnson, Keith Hentel, 2019, Annals of Internal Medicine.

Can Radiologists Learn From Airport Baggage Screening?: A Survey About Using Fictional Patients for Quality Assurance.

Emily M. Webb, Andrew S Phelps, D. Naeger, 2017, Academic radiology.

Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer.

Amie Y Lee, J. Mongan, N. Hylton, 2022, Radiology.

Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer.

Amie Y Lee, N. Hylton, Kimberly M Ray, 2023, Radiology.

Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities

J. Mongan, M. Aboian, I. Ikuta, 2022, Cancers.

In vivo comparison of tantalum, tungsten, and bismuth enteric contrast agents to complement intravenous iodine for double-contrast dual-energy CT of the bowel.

J. Mongan, B. Yeh, A. Torres, 2016, Contrast media & molecular imaging.

In vivo differentiation of complementary contrast media at dual-energy CT.

Benjamin M Yeh, John Mongan, Ella F Jones, 2012, Radiology.