John Mongan, MD, PhD

Professor
Associate Chair, Translational Informatics
Professor Clinical Radiology

Biography

John Mongan, MD, PhD, is the Associate Chair for Translational Informatics, Director of the Center for Intelligent Imaging and an Associate Professor of Clinical Radiology (Abdominal Imaging and Ultrasound section) in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco. He is board certified in both diagnostic radiology and clinical informatics.

His research focuses on artificial intelligence in medical imaging. He was the senior author and primary investigator on a project that developed artificial intelligence for the detection of pneumothorax (collapsed lung); in partnership with General Electric, the algorithm developed in this project achieved FDA clearance and is currently commercially available on portable X-ray machines. He is the lead author on the Checklist for Artificial Intelligence in Medical Imaging (CLAIM), a guideline used by several journals to promote reproducibility in artificial intelligence publications, and is the lead author on a publication drawing lessons for the safe implementation of artificial intelligence in medicine from the 737 Max disasters.

Dr. Mongan is nationally and internationally recognized as a leader and expert in artificial intelligence and machine learning. He chairs the Machine Learning Steering Committee of the Radiological Society of North America (RSNA, the world’s largest radiology specialty society). Through this committee, he organizes the assembly and curation of large multi-institutional medical imaging datasets and artificial intelligence contests using these datasets. These contests, conducted twice per year, attract over a thousand entrants. He serves on the editorial board of the journal Radiology: Artificial Intelligence, and represents the RSNA in organizing the national AI Safety Summit to be held for the first time in 2022. He has lectured on artificial intelligence at the annual meetings of the German Congress of Radiology, the Colombian Congress of Radiology, the international Medical Image Computing and Computer Assisted Intervention Society (MICCAI), and the RSNA.

Dr. Mongan also leads the University of California-wide effort to implement a clinical decision support system for ordering imaging that is compliant with the Protecting Access to Medicare Act (PAMA). He successfully obtained certification from the Center for Medicare and Medicaid Services (CMS) for the University of California to be recognized as a Qualified Provider Led Entity (QPLE) , able to create imaging appropriate use criteria (AUC) recognized as valid under PAMA. He chairs the UC QPLE steering committee, which has produced AUC covering six different clinical areas, available at qple.ucop.edu.

Education

2014 - Abdominal Imaging Fellowship, UC San Francisco
2013 - Radiology Residency, UC San Francisco
MD, 2008 - Medicine, UC San Diego
PhD, 2006 - Bioinformatics, UC San Diego
BS, 1999 - Chemistry, Stanford

Honors and Awards

Margulis Society Outstanding Resident Researcher, UCSF, 2013
Outstanding Academic Accomplishments, UCSD, 2008
Free Clinic Leadership Award, UCSD, 2008
Student Research Achievement Award, Biophysical Society, 2005

Publications

Fields BKK, Calabrese E, Mongan J, Cha S, Hess CP, Sugrue LP, Chang SM, Luks TL, Villanueva-Meyer JE, Rauschecker AM, Rudie JD. The University of California San Francisco Adult Longitudinal Post-Treatment Diffuse Glioma (UCSF-ALPTDG) MRI Dataset. Radiol Artif Intell. 2024 Jun 12; e230182.
Tejani AS, Klontzas ME, Gatti AA, Mongan JT, Moy L, Park SH, Kahn CE, CLAIM 2024 Update Panel. Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update. Radiol Artif Intell. 2024 May 29; e240300.
Huisman M, Kitamura FC, Mongan J, Yanagawa M. The Global Reading Room: Purchasing a Radiology Artificial Intelligence System. AJR Am J Roentgenol. 2024 Apr 10.
Kitamura FC, Prevedello LM, Colak E, Halabi SS, Lungren MP, Ball R, Kalpathy-Cramer J, Kahn CE, Richards T, Talbott JF, Shih G, Lin HM, Andriole KP, Vazirabad M, Erickson BJ, Flanders AE, Mongan J. Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges. Radiol Artif Intell. 2024 Mar 13; e230227.
Rudie JD, Saluja R, Weiss DA, Nedelec P, Calabrese E, Colby JB, Laguna B, Mongan J, Braunstein S, Hess CP, Rauschecker AM, Sugrue LP, Villanueva-Meyer JE. The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset. Radiol Artif Intell. 2024 Mar; 6(2):e230126.
Larson DB, Doo FX, Allen B, Mongan J, Flanders AE, Wald C. Proceedings From the 2022 ACR-RSNA Workshop on Safety, Effectiveness, Reliability, and Transparency in AI. J Am Coll Radiol. 2024 Feb 13.
Brady AP, Allen B, Chong J, Kotter E, Kottler N, Mongan J, Oakden-Rayner L, Pinto Dos Santos D, Tang A, Wald C, Slavotinek J. Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA. J Am Coll Radiol. 2024 Jan 23.
Brady AP, Allen B, Chong J, Kotter E, Kottler N, Mongan J, Oakden-Rayner L, Pinto Dos Santos D, Tang A, Wald C, Slavotinek J. Developing, purchasing, implementing and monitoring AI tools in radiology: Practical considerations. A multi-society statement from the ACR, CAR, ESR, RANZCR & RSNA. J Med Imaging Radiat Oncol. 2024 Feb; 68(1):7-26.
Brady AP, Allen B, Chong J, Kotter E, Kottler N, Mongan J, Oakden-Rayner L, Dos Santos DP, Tang A, Wald C, Slavotinek J. Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement From the ACR, CAR, ESR, RANZCR & RSNA. Can Assoc Radiol J. 2024 May; 75(2):226-244.
Brady AP, Allen B, Chong J, Kotter E, Kottler N, Mongan J, Oakden-Rayner L, Dos Santos DP, Tang A, Wald C, Slavotinek J. Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA. Radiol Artif Intell. 2024 Jan; 6(1):e230513.
Rohan Shad, Cyril R Zakka, Dhamanpreet Kaur, JOHN MONGAN, Kimberly G Kallianos, Ross Filice, Nishith Khandwala, David Eng, Curtis Langlotz, William Hiesinger. Abstract 13588: A Generalizable Deep Learning System for Cardiac MRI. Circulation. 2023 Nov 7; 148(Suppl_1).
Ali S. Tejani, Michail E. Klontzas, Anthony A. Gatti, John Mongan, Linda Moy, Seong Ho Park, Charles E. Kahn. Updating the Checklist for Artificial Intelligence in Medical Imaging (CLAIM) for reporting AI research. Nature Machine Intelligence. 2023 Sep 1; 5(9):950-951.
Mongan J, Halabi SS. On the Centrality of Data: Data Resources in Radiologic Artificial Intelligence. Radiol Artif Intell. 2023 Sep; 5(5):e230231.
Sebro R, Mongan J. TotalSegmentator: A Gift to the Biomedical Imaging Community. Radiol Artif Intell. 2023 Sep; 5(5):e230235.
Chung M, Calabrese E, Mongan J, Ray KM, Hayward JH, Kelil T, Sieberg R, Hylton N, Joe BN, Lee AY. Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer. Radiology. 2023 Mar; 306(3):e239004.
Grouse CK, Waung MW, Holmgren AJ, Mongan J, Neinstein A, Josephson SA, Khanna RR. Behavioral "nudges" in the electronic health record to reduce waste and misuse: 3 interventions. J Am Med Inform Assoc. 2023 02 16; 30(3):545-550.
Cacciamani GE, Chu TN, Sanford DI, Abreu A, Duddalwar V, Oberai A, Kuo CJ, Liu X, Denniston AK, Vasey B, McCulloch P, Wolff RF, Mallett S, Mongan J, Kahn CE, Sounderajah V, Darzi A, Dahm P, Moons KGM, Topol E, Collins GS, Moher D, Gill IS, Hung AJ. PRISMA AI reporting guidelines for systematic reviews and meta-analyses on AI in healthcare. Nat Med. 2023 01; 29(1):14-15.
Chung M, Calabrese E, Mongan J, Ray KM, Hayward JH, Kelil T, Sieberg R, Hylton N, Joe BN, Lee AY. Deep Learning to Simulate Contrast-enhanced Breast MRI of Invasive Breast Cancer. Radiology. 2023 03; 306(3):e213199.
Mongan J, Kohli MD, Houshyar R, Chang PD, Glavis-Bloom J, Taylor AG. Automated detection of IVC filters on radiographs with deep convolutional neural networks. Abdom Radiol (NY). 2023 02; 48(2):758-764.
Calabrese E, Villanueva-Meyer JE, Rudie JD, Rauschecker AM, Baid U, Bakas S, Cha S, Mongan JT, Hess CP. The University of California San Francisco Preoperative Diffuse Glioma MRI Dataset. Radiol Artif Intell. 2022 Nov; 4(6):e220058.
Lakhani P, Mongan J, Singhal C, Zhou Q, Andriole KP, Auffermann WF, Prasanna PM, Pham TX, Peterson M, Bergquist PJ, Cook TS, Ferraciolli SF, Corradi GCA, Takahashi MS, Workman CS, Parekh M, Kamel SI, Galant J, Mas-Sanchez A, Benítez EC, Sánchez-Valverde M, Jaques L, Panadero M, Vidal M, Culiañez-Casas M, Angulo-Gonzalez D, Langer SG, de la Iglesia-Vayá M, Shih G. The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs. J Digit Imaging. 2023 02; 36(1):365-372.
Karandikar A, Solberg A, Fung A, Lee AY, Farooq A, Taylor AC, Oliveira A, Narayan A, Senter A, Majid A, Tong A, McGrath AL, Malik A, Brown AL, Roberts A, Fleischer A, Vettiyil B, Zigmund B, Park B, Curran B, Henry C, Jaimes C, Connolly C, Robson C, Meltzer CC, Phillips CH, Dove C, Glastonbury C, Pomeranz C, Kirsch CFE, Burgan CM, Scher C, Tomblinson C, Fuss C, Santillan C, Daye D, Brown DB, Young DJ, Kopans D, Vargas D, Martin D, Thompson D, Jordan DW, Shatzkes D, Sun D, Mastrodicasa D, Smith E, Korngold E, Dibble EH, Arleo EK, Hecht EM, Morris E, Maltin EP, Cooke EA, Schwartz ES, Lehrman E, Sodagari F, Shah F, Doo FX, Rigiroli F, Vilanilam GK, Landinez G, Kim GG, Rahbar H, Choi H, Bandesha H, Ojeda-Fournier H, Ikuta I, Dragojevic I, Schroeder JLT, Ivanidze J, Katzen JT, Chiang J, Nguyen J, Robinson JD, Broder JC, Kemp J, Weaver JS, Conyers JM, Robbins JB, Leschied JR, Wen J, Park J, Mongan J, Perchik J, Barbero JPM, Jacob J, Ledbetter K, Macura KJ, Maturen KE, Frederick-Dyer K, Dodelzon K, Cort K, Kisling K, Babagbemi K, McGill KC, Chang KJ, Feigin K, Winsor KS, Seifert K, Patel K, Porter KK, Foley KM, Patel-Lippmann K, McIntosh LJ, Padilla L, Groner L, Harry LM, Ladd LM, Wang L, Spalluto LB, Mahesh M, Marx MV, Sugi MD, Sammer MBK, Sun M, Barkovich MJ, Miller MJ, Vella M, Davis MA, Englander MJ, Durst M, Oumano M, Wood MJ, McBee MP, Fischbein NJ, Kovalchuk N, Lall N, Eclov N, Madhuripan N, Ariaratnam NS, Vincoff NS, Kothary N, Yahyavi-Firouz-Abadi N, Brook OR, Glenn OA, Woodard PK, Mazaheri P, Rhyner P, Eby PR, Raghu P, Gerson RF, Patel R, Gutierrez RL, Gebhard R, Andreotti RF, Masum R, Woods R, Mandava S, Harrington SG, Parikh S, Chu S, Arora SS, Meyers SM, Prabhu S, Shams S, Pittman S, Patel SN, Payne S, Hetts SW, Hijaz TA, Chapman T, Loehfelm TW, Juang T, Clark TJ, Potigailo V, Shah V, Planz V, Kalia V, DeMartini W, Dillon WP, Gupta Y, Koethe Y, Hartley-Blossom Z, Wang ZJ, McGinty G, Haramati A, Allen LM, Germaine P. Radiologists staunchly support patient safety and autonomy, in opposition to the SCOTUS decision to overturn Roe v Wade. Clin Imaging. 2023 01; 93:117-121.
Wang RC, Fahimi J, Dillon D, Shyy W, Mongan J, McCulloch C, Smith-Bindman R. Effect of an ultrasound-first clinical decision tool in emergency department patients with suspected nephrolithiasis: A randomized trial. Am J Emerg Med. 2022 10; 60:164-170.
Merkaj S, Bahar RC, Zeevi T, Lin M, Ikuta I, Bousabarah K, Cassinelli Petersen GI, Staib L, Payabvash S, Mongan JT, Cha S, Aboian MS. Machine Learning Tools for Image-Based Glioma Grading and the Quality of Their Reporting: Challenges and Opportunities. Cancers (Basel). 2022 May 25; 14(11).
Mongan J, Vagal A, Wu CC. Imaging AI in Practice: Introducing the Special Issue. Radiol Artif Intell. 2022 Mar; 4(2):e220039.
Webb EM, Mongan J. Gastrointestinal Stromal Tumors: Radiomics may Increase the Role of Imaging in Malignant Risk Assessment. Acad Radiol. 2022 06; 29(6):817-818.
Mongan J, Kalpathy-Cramer J, Flanders A, George Linguraru M. RSNA-MICCAI Panel Discussion: Machine Learning for Radiology from Challenges to Clinical Applications. Radiol Artif Intell. 2021 Sep; 3(5):e210118.
Eng D, Chute C, Khandwala N, Rajpurkar P, Long J, Shleifer S, Khalaf MH, Sandhu AT, Rodriguez F, Maron DJ, Seyyedi S, Marin D, Golub I, Budoff M, Kitamura F, Takahashi MS, Filice RW, Shah R, Mongan J, Kallianos K, Langlotz CP, Lungren MP, Ng AY, Patel BN. Automated coronary calcium scoring using deep learning with multicenter external validation. NPJ Digit Med. 2021 Jun 01; 4(1):88.
Colak E, Kitamura FC, Hobbs SB, Wu CC, Lungren MP, Prevedello LM, Kalpathy-Cramer J, Ball RL, Shih G, Stein A, Halabi SS, Altinmakas E, Law M, Kumar P, Manzalawi KA, Nelson Rubio DC, Sechrist JW, Germaine P, Lopez EC, Amerio T, Gupta P, Jain M, Kay FU, Lin CT, Sen S, Revels JW, Brussaard CC, Mongan J, RSNA-STR Annotators and Dataset Curation Contributors. The RSNA Pulmonary Embolism CT Dataset. Radiol Artif Intell. 2021 Mar; 3(2):e200254.
Tsai EB, Simpson S, Lungren MP, Hershman M, Roshkovan L, Colak E, Erickson BJ, Shih G, Stein A, Kalpathy-Cramer J, Shen J, Hafez M, John S, Rajiah P, Pogatchnik BP, Mongan J, Altinmakas E, Ranschaert ER, Kitamura FC, Topff L, Moy L, Kanne JP, Wu CC. The RSNA International COVID-19 Open Radiology Database (RICORD). Radiology. 2021 04; 299(1):E204-E213.
Filice RW, Mongan J, Kohli MD. Evaluating Artificial Intelligence Systems to Guide Purchasing Decisions. J Am Coll Radiol. 2020 Nov; 17(11):1405-1409.
Flanders AE, Prevedello LM, Shih G, Halabi SS, Kalpathy-Cramer J, Ball R, Mongan JT, Stein A, Kitamura FC, Lungren MP, Choudhary G, Cala L, Coelho L, Mogensen M, Morón F, Miller E, Ikuta I, Zohrabian V, McDonnell O, Lincoln C, Shah L, Joyner D, Agarwal A, Lee RK, Nath J, RSNA-ASNR 2019 Brain Hemorrhage CT Annotators. Erratum: Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge. Radiol Artif Intell. 2020 Jul; 2(4):e209002.
Houshyar R, Tran-Harding K, Glavis-Bloom J, Nguyentat M, Mongan J, Chahine C, Loehfelm TW, Kohli MD, Zaragoza EJ, Murphy PM, Kampalath R. Effect of shelter-in-place on emergency department radiology volumes during the COVID-19 pandemic. Emerg Radiol. 2020 Dec; 27(6):781-784.
Flanders AE, Prevedello LM, Shih G, Halabi SS, Kalpathy-Cramer J, Ball R, Mongan JT, Stein A, Kitamura FC, Lungren MP, Choudhary G, Cala L, Coelho L, Mogensen M, Morón F, Miller E, Ikuta I, Zohrabian V, McDonnell O, Lincoln C, Shah L, Joyner D, Agarwal A, Lee RK, Nath J, RSNA-ASNR 2019 Brain Hemorrhage CT Annotators. Construction of a Machine Learning Dataset through Collaboration: The RSNA 2019 Brain CT Hemorrhage Challenge. Radiol Artif Intell. 2020 May; 2(3):e190211.
Mongan J, Moy L, Kahn CE. Checklist for Artificial Intelligence in Medical Imaging (CLAIM): A Guide for Authors and Reviewers. Radiol Artif Intell. 2020 Mar; 2(2):e200029.
Mongan J, Kohli M. Artificial Intelligence and Human Life: Five Lessons for Radiology from the 737 MAX Disasters. Radiol Artif Intell. 2020 Mar; 2(2):e190111.
Hentel KD, Menard A, Mongan J, Durack JC, Raja AS, Khorasani R. Mandated Imaging Appropriate Use Criteria. Ann Intern Med. 2019 11 05; 171(9):682-683.
Hentel KD, Menard A, Mongan J, Durack JC, Johnson PT, Raja AS, Khorasani R. What Physicians and Health Organizations Should Know About Mandated Imaging Appropriate Use Criteria. Ann Intern Med. 2019 06 18; 170(12):880-885.
Fahimi J, Kanzaria HK, Mongan J, Kahn KL, Wang RC. Potential Effect of the Protecting Access to Medicare Act on Use of Advanced Diagnostic Imaging in the Emergency Department: An Analysis of the National Hospital Ambulatory Care Survey. Radiology. 2019 04; 291(1):188-193.
Kallianos K, Mongan J, Antani S, Henry T, Taylor A, Abuya J, Kohli M. How far have we come? Artificial intelligence for chest radiograph interpretation. Clin Radiol. 2019 05; 74(5):338-345.
Taylor AG, Mielke C, Mongan J. Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study. PLoS Med. 2018 11; 15(11):e1002697.
Mongan J, Avrin D. Impact of PACS-EMR Integration on Radiologist Usage of the EMR. J Digit Imaging. 2018 10; 31(5):611-614.
Marcus SG, Candia S, Kohli MD, Mongan J, Zagoria RJ, Behr SC, Sun D, Westphalen AC. Association between misty mesentery with baseline or new diagnosis of cancer: a matched cohort study. Clin Imaging. 2018 Jul - Aug; 50:57-61.
Phelps A, Callen AL, Marcovici P, Naeger DM, Mongan J, Webb EM. Can Radiologists Learn From Airport Baggage Screening?: A Survey About Using Fictional Patients for Quality Assurance. Acad Radiol. 2018 02; 25(2):226-234.
Kovacs MD, Mesterhazy J, Avrin D, Urbania T, Mongan J. Correlate: A PACS- and EHR-integrated Tool Leveraging Natural Language Processing to Provide Automated Clinical Follow-up. Radiographics. 2017 Sep-Oct; 37(5):1451-1460.
Chi T, Usawachintachit M, Weinstein S, Kohi MP, Taylor A, Tzou DT, Chang HC, Stoller M, Mongan J. Contrast Enhanced Ultrasound as a Radiation-Free Alternative to Fluoroscopic Nephrostogram for Evaluating Ureteral Patency. J Urol. 2017 12; 198(6):1367-1373.
Thomas Chi, Manint Usawachintachit, David Tzou, Helena Chang, Benjamin Sherer, Marshall Stoller, Stefanie Weinstein, John Mongan. PD11-05 CONTRAST-ENHANCED ULTRASOUND AS A REPLACEMENT FOR FLUOROSCOPIC NEPHROSTOGRAM FOLLOWING PERCUTANEOUS NEPHROLITHOTOMY. The Journal of Urology. 2017 Apr 1; 197(4):e207-e208.
Rajkomar A, Lingam S, Taylor AG, Blum M, Mongan J. High-Throughput Classification of Radiographs Using Deep Convolutional Neural Networks. J Digit Imaging. 2017 02; 30(1):95-101.
Tzou DT, Weinstein S, Usawachintachit M, Mongan J, Greene KL, Chi T. Contrast Enhanced Ultrasound Detects Recurrent Renal Cell Carcinoma in the Setting of Chronic Renal Insufficiency. Clin Genitourin Cancer. 2017 08; 15(4):e735-e737.
Usawachintachit M, Tzou DT, Mongan J, Taguchi K, Weinstein S, Chi T. Feasibility of Retrograde Ureteral Contrast Injection to Guide Ultrasonographic Percutaneous Renal Access in the Nondilated Collecting System. J Endourol. 2017 02; 31(2):129-134.
Usawachintachit M, Tzou DT, Mongan J, Weinstein S, Chi T. Antegrade ultrasound contrast injection facilitates accurate nephrostomy tube positioning during percutaneous nephrolithotomy. Int J Urol. 2017 03; 24(3):239-240.
Chi T, Usawachintachit M, Mongan J, Kohi MP, Taylor A, Jha P, Chang HC, Stoller M, Goldstein R, Weinstein S. Feasibility of Antegrade Contrast-enhanced US Nephrostograms to Evaluate Ureteral Patency. Radiology. 2017 04; 283(1):273-279.
Mongan J, Sebro R. Definition of Confidence Interval. Radiographics. 2016 Sep-Oct; 36(5):1602.
Li Y, Mongan J, Behr SC, Sud S, Coakley FV, Simko J, Westphalen AC. Beyond Prostate Adenocarcinoma: Expanding the Differential Diagnosis in Prostate Pathologic Conditions. Radiographics. 2016 Jul-Aug; 36(4):1055-75.
Manint Usawachintachit, John Mongan, Matthew Truesdale, Stefanie Weinstein, Thomas Chi. PD14-01 CAN CONTRAST-ENHANCED ULTRASOUND REPLACE FLUOROSCOPIC NEPHROSTOGRAM?. The Journal of Urology. 2016 Apr 1; 195(4):e302-e303.
Rathnayake S, Mongan J, Torres AS, Colborn R, Gao DW, Yeh BM, Fu Y. In vivo comparison of tantalum, tungsten, and bismuth enteric contrast agents to complement intravenous iodine for double-contrast dual-energy CT of the bowel. Contrast Media Mol Imaging. 2016 07; 11(4):254-61.
Mongan J, Kline J, Smith-Bindman R. Age and sex-dependent trends in pulmonary embolism testing and derivation of a clinical decision rule for young patients. Emerg Med J. 2015 Nov; 32(11):840-5.
Yu JP, Kansagra AP, Mongan J. The radiologist's workflow environment: evaluation of disruptors and potential implications. J Am Coll Radiol. 2014 Jun; 11(6):589-93.
Mongan J, Rathnayake S, Fu Y, Gao DW, Yeh BM. Extravasated contrast material in penetrating abdominopelvic trauma: dual-contrast dual-energy CT for improved diagnosis--preliminary results in an animal model. Radiology. 2013 Sep; 268(3):738-42.
Coakley FV, Hanley-Knutson K, Mongan J, Barajas R, Bucknor M, Qayyum A. Pancreatic imaging mimics: part 1, imaging mimics of pancreatic adenocarcinoma. AJR Am J Roentgenol. 2012 Aug; 199(2):301-8.
Mongan J, Rathnayake S, Fu Y, Wang R, Jones EF, Gao DW, Yeh BM. In vivo differentiation of complementary contrast media at dual-energy CT. Radiology. 2012 Oct; 265(1):267-72.
Mongan J, Mieszczanska HZ, Smith BH, Messing SP, Phipps RP, Francis CW. Pioglitazone inhibits platelet function and potentiates the effects of aspirin: a prospective observation study. Thromb Res. 2012 Jun; 129(6):760-4.
Mongan J, Svrcek-Seiler WA, Onufriev A. Analysis of integral expressions for effective Born radii. J Chem Phys. 2007 Nov 14; 127(18):185101.
Mongan J, Simmerling C, McCammon JA, Case DA, Onufriev A. Generalized Born model with a simple, robust molecular volume correction. J Chem Theory Comput. 2007 Jan 01; 3(1):156-169.
Lewis JA, Mongan J, McCammon JA, Cohen SM. Evaluation and binding-mode prediction of thiopyrone-based inhibitors of anthrax lethal factor. ChemMedChem. 2006 Jul; 1(7):694-7.
Puerta DT, Mongan J, Tran BL, McCammon JA, Cohen SM. Potent, selective pyrone-based inhibitors of stromelysin-1. J Am Chem Soc. 2005 Oct 19; 127(41):14148-9.
Swanson JM, Mongan J, McCammon JA. Limitations of atom-centered dielectric functions in implicit solvent models. J Phys Chem B. 2005 Aug 11; 109(31):14769-72.
Mongan J, Case DA. Biomolecular simulations at constant pH. Curr Opin Struct Biol. 2005 Apr; 15(2):157-63.
Mongan J, Case DA, McCammon JA. Constant pH molecular dynamics in generalized Born implicit solvent. J Comput Chem. 2004 Dec; 25(16):2038-48.
Hamelberg D, Mongan J, McCammon JA. Accelerated molecular dynamics: a promising and efficient simulation method for biomolecules. J Chem Phys. 2004 Jun 22; 120(24):11919-29.
Mongan J. Interactive essential dynamics. J Comput Aided Mol Des. 2004 Jun; 18(6):433-6.