Rashmee U. Shah
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Rashmee U. Shah, MD, MS

Languages spoken: English

  • Dr. Rashmee Shah is an Assistant Professor in Cardiovascular Medicine at the University of Utah School of Medicine. Dr. Shah’s research focuses on clinical applications of data science, machine learning, and natural language processing. Specifically, her current projects focus on: 1) phenotyping atrial fibrillation patients using natural language processing and big data analyses 2) predicting readmission after acute myocardial infarction with machine learning methods, incorporating socioeconomic status 3) predicting complications following cardiac surgery using neural networks, incorporating functional status derived using an ontology. The overall goal of Dr. Shah's work is to find the right treatments for the right patients, and maximize benefit while minimizing harm.

    Dr. Shah's research has been published in high impact journals, including the Journal of the American College of Cardiology and JAMA Network Open. She served as the Chair of the Young Clinicians and Investigators Committee, a part of the Council on Quality of Care and Outcomes, American Heart Association. Dr. Shah participates on the Research and Publications committees of the NCDR (National Cardiovascular Data Registry), the Informatics and Health IT Task Force, and Cardiovascular Diseases in Women Committee of the American College of Cardiology. Dr. Shah is the recipient of several honors, including membership in the Alpha Omega Alpha Honor Medical Society, the American Heart Association Excellence in Training Award, and research support from the National Institutes of Health.

    Finally, a key goal for Dr. Shah is to increase the presence of women in leadership and authority roles in cardiovascular medicine. She supports this goal through speaking engagements as well as an editorial published in JAMA Cardiology.

    Dr. Shah received her medical degree at the Tufts University School of Medicine, where she graduated with honors. She completed Internal Medicine Residency at Northwestern University and then went on to complete a postdoctoral fellowship and Master’s degree in Health Services Research at Stanford University. Dr. Shah completed her cardiology training at Cedars-Sinai Medical Center and the University of Pittsburgh. She has also received a Certificate in Biomedical Informatics at the University of Utah. Her clinical interests include echocardiography, acute cardiac care, and data and information systems to improve health care outcomes.

    Rashmee U. Shah, MD MS is an Assistant Professor in Cardiovascular Medicine in the Department of Internal Medicine at the University of Utah School of Medicine. She has been on tenure track faculty at the University of Utah since 2014.

    Nationally, she chairs the Young Investigators Committee and is on the Leadership Council for the American Heart Association Council on Quality of Care and Outcomes Research. Cardiology Today recently named her a “NextGen Innovator.” She is the recipient of grant support from the National Heart, Lung, and Blood Institute and is focused on practical applications of data science. Specifically, she is developing a clinically useful tool for information extraction from the electronic health record, focused on patient safety.

    Specialties

    Board Certification

    American Board of Internal Medicine (Internal Medicine)
    American Board of Internal Medicine (Sub: Cardiovascular Disease)
    Certification Board of Cardiovascular Computed Tomography
    National Board of Echocardiography

  • Dr. Rashmee Shah is an Assistant Professor in Cardiovascular Medicine at the University of Utah School of Medicine. Dr. Shah’s research focuses on clinical applications of data science, machine learning, and natural language processing. Specifically, her current projects focus on: 1) phenotyping atrial fibrillation patients using natural language processing and big data analyses 2) predicting readmission after acute myocardial infarction with machine learning methods, incorporating socioeconomic status 3) predicting complications following cardiac surgery using neural networks, incorporating functional status derived using an ontology. The overall goal of Dr. Shah's work is to find the right treatments for the right patients, and maximize benefit while minimizing harm.

    Dr. Shah's research has been published in high impact journals, including the Journal of the American College of Cardiology and JAMA Network Open. She served as the Chair of the Young Clinicians and Investigators Committee, a part of the Council on Quality of Care and Outcomes, American Heart Association. Dr. Shah participates on the Research and Publications committees of the NCDR (National Cardiovascular Data Registry), the Informatics and Health IT Task Force, and Cardiovascular Diseases in Women Committee of the American College of Cardiology. Dr. Shah is the recipient of several honors, including membership in the Alpha Omega Alpha Honor Medical Society, the American Heart Association Excellence in Training Award, and research support from the National Institutes of Health.

    Finally, a key goal for Dr. Shah is to increase the presence of women in leadership and authority roles in cardiovascular medicine. She supports this goal through speaking engagements as well as an editorial published in JAMA Cardiology.

    Dr. Shah received her medical degree at the Tufts University School of Medicine, where she graduated with honors. She completed Internal Medicine Residency at Northwestern University and then went on to complete a postdoctoral fellowship and Master’s degree in Health Services Research at Stanford University. Dr. Shah completed her cardiology training at Cedars-Sinai Medical Center and the University of Pittsburgh. She has also received a Certificate in Biomedical Informatics at the University of Utah. Her clinical interests include echocardiography, acute cardiac care, and data and information systems to improve health care outcomes.

    Rashmee U. Shah, MD MS is an Assistant Professor in Cardiovascular Medicine in the Department of Internal Medicine at the University of Utah School of Medicine. She has been on tenure track faculty at the University of Utah since 2014.

    Nationally, she chairs the Young Investigators Committee and is on the Leadership Council for the American Heart Association Council on Quality of Care and Outcomes Research. Cardiology Today recently named her a “NextGen Innovator.” She is the recipient of grant support from the National Heart, Lung, and Blood Institute and is focused on practical applications of data science. Specifically, she is developing a clinically useful tool for information extraction from the electronic health record, focused on patient safety.

    Board Certification and Academic Information

    Academic Departments Internal Medicine -Adjunct
    Academic Divisions Cardiovascular Medicine
    Board Certification
    American Board of Internal Medicine (Internal Medicine)
    American Board of Internal Medicine (Sub: Cardiovascular Disease)
    Certification Board of Cardiovascular Computed Tomography
    National Board of Echocardiography

    Education history

    Certification Biomedical Informatics - University of Utah Certificate
    Fellowship Cardiology - University of Pittsburgh Medical Center Fellow
    Fellowship Cardiology - Cedars Sinai Medical Center/GLA VA Medical Center Fellow
    Graduate Training Health Services Research - Stanford University M.S.
    Postdoctoral Fellowship Health Research & Policy - Stanford University Postdoctoral Fellow
    Residency Internal Medicine - Northwestern University/Jesse Brown VA Hospital Resident
    Professional Medical Medicine - Tufts University School of Medicine M.D.
    Undergraduate Environmental Sciences - Northwestern University B.A.

    Selected Publications

    Journal Article

    1. Brown JR, Ricket IM, Reeves RM, Shah RU, Goodrich CA, Gobbel G, Stabler ME, Perkins AM, Minter F, Cox KC, Dorn C, Denton J, Bray BE, Gouripeddi R, Higgins J, Chapman WW, MacKenzie T, Matheny ME (2022). Information Extraction From Electronic Health Records to Predict Readmission Following Acute Myocardial Infarction: Does Natural Language Processing Using Clinical Notes Improve Prediction of Readmission? J Am Heart Assoc, 11(7), e024198. (Read full article)
    2. Shah KS, Reyes-Miranda AE, Bradley SM, Breathett K, Das SR, Gluckman TJ, Gupta D, Leung DT, Mutharasan RK, Peterson PN, Spivak ES, Shah RU (2022). Clinical Trial Participation and COVID-19: a Descriptive Analysis from the American Heart Association's Get With The Guidelines Registry. J Racial Ethn Health Disparities. (Read full article)
    3. Jacobs JA, Shah RU, Bress AP (2022). Asymptomatic hypertension in the hospital setting: primum non nocere. J Hum Hypertens, 36, 781-784. (Read full article)
    4. Wesoowski S, Lemmon G, Hernandez EJ, Henrie A, Miller TA, Weyhrauch D, Puchalski MD, Bray BE, Shah RU, Deshmukh VG, Delaney R, Yostl HJ, Eilbeck K, Tristani-Firouzi M, Yandell M (2022). An explainable artificial intelligence approach for predicting cardiovascular outcomes using electronic health records. PLOS Digit Health, 1(1). (Read full article)
    5. Steinberg BA, Li Z, Shrader P, Chew DS, Bunch TJ, Mark DB, Nabutovsky Y, Shah RU, Greiner MA, Piccini JP (2021). Clinical Investigations Bimodal Distribution of Atrial Fibrillation Burden in 3 Distinct Cohorts: What is 'Paroxysmal' Atrial Fibrillation? Am Heart J, 244, 149-156. (Read full article)
    6. Reimer JR, Ahmed SM, Brintz BJ, Shah RU, Keegan LT, Ferrari MJ, Leung DT (2021). The Effects of Using a Clinical Prediction Rule to Prioritize Diagnostic Testing on Transmission and Hospital Burden: A Modeling Example of Early Severe Acute Respiratory Syndrome Coronavirus 2. Clin Infect Dis, 73(10), 1822-1830. (Read full article)
    7. Wohlfahrt P, Nativi-Nicolau J, Zhang M, Selzman CH, Greene T, Conte J, Biber JE, Hess R, Mondesir FL, Wever-Pinzon O, Drakos SG, Gilbert EM, Kemeyou L, LaSalle B, Steinberg BA, Shah RU, Fang JC, Spertus JA, Stehlik J (2022). Quality of Life in Patients With Heart Failure With Recovered Ejection Fraction. JAMA Cardiol, 6(8), 957-962. (Read full article)
    8. Reeves RM, Christensen L, Brown JR, Conway M, Levis M, Gobbel GT, Shah RU, Goodrich C, Ricket I, Minter F, Bohm A, Bray BE, Matheny ME, Chapman W (2021). Adaptation of an NLP system to a new healthcare environment to identify social determinants of health. J Biomed Inform, 120, 103851. (Read full article)
    9. Bradley SM, Emmons-Bell S, Mutharasan RK, Rodriguez F, Gupta D, Roth G, Gluckman TJ, Shah RU, Wang TY, Khera R, Peterson PN, Das S (2021). Repeated cross-sectional analysis of hydroxychloroquine deimplementation in the AHA COVID-19 CVD Registry. Sci Rep, 11(1), 15097. (Read full article)
    10. Sturm RC, Jones TL, Youngquist ST, Shah RU (2021). Regional Systems of Care in ST Elevation Myocardial Infarction. Interv Cardiol Clin, 10(3), 281-291. (Read full article)
    11. Goyal N, Herrick JS, Son S, Metz TD, Shah RU (2019). Maternal cardiovascular complications at the time of delivery and subsequent re-hospitalization in the USA, 2010-16. Eur Heart J Qual Care Clin Outcomes, 7(3), 304-311. (Read full article)
    12. Wang L, Nielsen K, Goldberg J, Brown JR, Rumsfeld JS, Steinberg BA, Zhang Y, Matheny ME, Shah RU (2021). Association of Wearable Device Use With Pulse Rate and Health Care Use in Adults With Atrial Fibrillation. JAMA Netw Open, 4(5), e215821. (Read full article)
    13. Ahmed SM, Shah RU, Fernandez V, Grineski S, Brintz B, Samore MH, Ferrari MJ, Leung DT, Keegan LT (2021). Robust Testing in Outpatient Settings to Explore COVID-19 Epidemiology: Disparities in Race/Ethnicity and Age, Salt Lake County, Utah, 2020. Public Health Rep, 136(3), 345-353. (Read full article)
    14. Park K, Bairey Merz CN, Bello NA, Davis M, Duvernoy C, Elgendy IY, Ferdinand KC, Hameed A, Itchhaporia D, Minissian MB, Reynolds H, Mehta P, Russo AM, Shah RU, Volgman AS, Wei J, Wenger NK, Pepine CJ, Lindley KJ, American College of Cardiology Cardiovascular Disease in Women Committee and the Cardio-Obstetrics Work Group (2020). Management of Women With Acquired Cardiovascular Disease From Pre-Conception Through Pregnancy and Postpartum: JACC Focus Seminar 3/5. J Am Coll Cardiol, 77(14), 1799-1812. (Read full article)
    15. Shao Y, Cheng Y, Shah RU, Weir CR, Bray BE, Zeng-Treitler Q (2021). Shedding Light on the Black Box: Explaining Deep Neural Network Prediction of Clinical Outcomes. J Med Syst, 45(1), 5. (Read full article)
    16. Matheny ME, Ricket I, Goodrich CA, Shah RU, Stabler ME, Perkins AM, Dorn C, Denton J, Bray BE, Gouripeddi R, Higgins J, Chapman WW, MacKenzie TA, Brown JR (2021). Development of Electronic Health Record-Based Prediction Models for 30-Day Readmission Risk Among Patients Hospitalized for Acute Myocardial Infarction. JAMA Netw Open, 4(1), e2035782. (Read full article)
    17. Zenger B, Swink JM, Turner JL, Bunch TJ, Ryan JJ, Shah RU, Turakhia MP, Piccini JP, Steinberg BA (2020). Social Media Influence Does Not Reflect Scholarly or Clinical Activity in Real Life. Circ Arrhythm Electrophysiol, 13(11), e008847. (Read full article)
    18. Shah RU, Mutharasan RK, Ahmad FS, Rosenblatt AG, Gay HC, Steinberg BA, Yandell M, Tristani-Firouzi M, Klewer J, Mukherjee R, Lloyd-Jones DM (2020). Development of a Portable Tool to Identify Patients With Atrial Fibrillation Using Clinical Notes From the Electronic Medical Record. Circ Cardiovasc Qual Outcomes, 13(10), e006516. (Read full article)
    19. Rumsfeld JS, Shah RU, Druz RS (2021). Innovation in Cardiology: The ACC Innovation Program. Methodist Debakey Cardiovasc J, 16(4), 304-308. (Read full article)
    20. Crabb BT, Lyons A, Bale M, Martin V, Berger B, Mann S, West WB Jr, Brown A, Peacock JB, Leung DT, Shah RU (2020). Comparison of International Classification of Diseases and Related Health Problems, Tenth Revision Codes With Electronic Medical Records Among Patients With Symptoms of Coronavirus Disease 2019. JAMA Netw Open, 3(8), e2017703. (Read full article)
    21. Shah RU (2020). We Don't Need More Data, We Need the Right Data. Circulation, 142(3), 197-198. (Read full article)
    22. Shah RU, Curtis LH (2020). Data Quarantine in the Time of the COVID-19 Pandemic. Circ Cardiovasc Qual Outcomes, 13(6), e006908. (Read full article)
    23. Turner JL, Lyons A, Shah RU, Zenger B, Hess R, Steinberg BA (2020). Accuracy of Patient Identification of Electrocardiogram-Verified Atrial Arrhythmias. JAMA Netw Open, 3(5), e205431. (Read full article)
    24. Shah RU, Mukherjee R, Zhang Y, Jones AE, Springer J, Hackett I, Steinberg BA, Lloyd-Jones DM, Chapman WW (2020). Impact of Different Electronic Cohort Definitions to Identify Patients With Atrial Fibrillation From the Electronic Medical Record. J Am Heart Assoc, 9(5), e014527. (Read full article)
    25. Steinberg BA, Turner J, Lyons A, Biber J, Chelu MG, Fang JC, Freedman RA, Han FT, Hardisty B, Marrouche NF, Ranjan R, Shah RU, Spertus JA, Stehlik J, Zenger B, Piccini JP, Hess R (2019). Systematic collection of patient-reported outcomes in atrial fibrillation: feasibility and initial results of the Utah mEVAL AF programme. Europace, 22(3), 368-374. (Read full article)
    26. Owlia M, Dodson JA, King JB, Derington CG, Herrick JS, Sedlis SP, Crook J, DuVall SL, LaFleur J, Nelson R, Patterson OV, Shah RU, Bress AP (2019). Angina Severity, Mortality, and Healthcare Utilization Among Veterans With Stable Angina. J Am Heart Assoc, 8(15), e012811. (Read full article)
    27. Chamberlain AM, Gong Y, Shaw KM, Bian J, Song WL, Linton MF, Fonseca V, Price-Haywood E, Guhl E, King JB, Shah RU, Puro J, Shenkman E, Pawloski PA, Margolis KL, Hernandez AF, Cooper-DeHoff RM (2019). PCSK9 Inhibitor Use in the Real World: Data From the National Patient-Centered Research Network. J Am Heart Assoc, 8(9), e011246. (Read full article)
    28. Doing-Harris K, Bray BE, Thackeray A, Shah RU, Shao Y, Cheng Y, Zeng-Treitler Q, Garvin JH, Weir C (2019). Development of a cardiac-centered frailty ontology. J Biomed Semantics, 10(1), 3. (Read full article)
    29. Selker HP, Kwong M, Ruthazer R, Gorman S, Green G, Patchen E, Udelson JE, Smithline HA, Baumann MR, Harris PA, Shah RU, Nelson SJ, Cohen T, Jones EB, Barnewolt BA, Williams AE (2019). An example of medical device-based projection of clinical trial enrollment: Use of electrocardiographic data to identify candidates for a trial in acute coronary syndromes. J Clin Transl Sci, 2(6), 377-383. (Read full article)
    30. Walker AL, Sorensen T, Gabriel PP, Sledge T, Morshedzadeh JH, Owan T, Shah RU (2018). Ticagrelor Use in Acute Myocardial Infarction: Balancing Evidence-Based Medicine with Affordability. J Am Coll Clin Pharm, 1(2), 58-61. (Read full article)
    31. Taggart M, Chapman WW, Steinberg BA, Ruckel S, Pregenzer-Wenzler A, Du Y, Ferraro J, Bucher BT, Lloyd-Jones DM, Rondina MT, Shah RU (2018). Comparison of 2 Natural Language Processing Methods for Identification of Bleeding Among Critically Ill Patients. JAMA Netw Open, 1(6), e183451. (Read full article)
    32. Shah RU (2018). The $2.5 Million Dollar Wage Gap in Cardiology. JAMA Cardiol, 3(8), 674-676. (Read full article)
    33. Mathews R, Wang W, Kaltenbach LA, Thomas L, Shah RU, Ali M, Peterson ED, Wang TY (2018). Hospital Variation in Adherence Rates to Secondary Prevention Medications and the Implications on Quality. Circulation, 137(20), 2128-2138. (Read full article)
    34. Humphries KH, Izadnegahdar M, Sedlak T, Saw J, Johnston N, Schenck-Gustafsson K, Shah RU, Regitz-Zagrosek V, Grewal J, Vaccarino V, Wei J, Bairey Merz CN (2017). Sex differences in cardiovascular disease - Impact on care and outcomes. Front Neuroendocrinol, 46, 46-70. (Read full article)
    35. King JB, Shah RU, Sainski-Nguyen A, Biskupiak J, Munger MA, Bress AP (2017). Effect of Inpatient Dobutamine versus Milrinone on Out-of-Hospital Mortality in Patients with Acute Decompensated Heart Failure. Pharmacotherapy, 37(6), 662-672. (Read full article)
    36. Shao Y, Mohanty AF, Ahmed A, Weir CR, Bray BE, Shah RU, Redd D, Zeng-Treitler Q (2016). Identification and Use of Frailty Indicators from Text to Examine Associations with Clinical Outcomes Among Patients with Heart Failure. AMIA Annu Symp Proc, 2016, 1110-1118. (Read full article)
    37. Ko BS, Drakos SG, Welt FGP, Shah RU (2016). Controversies and Challenges in the Management of ST-Elevation Myocardial Infarction Complicated by Cardiogenic Shock. Interv Cardiol Clin, 5(4), 541-549. (Read full article)
    38. Sutton NR, Li S, Thomas L, Wang TY, de Lemos JA, Enriquez JR, Shah RU, Fonarow GC (2016). The association of left ventricular ejection fraction with clinical outcomes after myocardial infarction: Findings from the Acute Coronary Treatment and Intervention Outcomes Network (ACTION) Registry-Get With the Guidelines (GWTG) Medicare-linked database. Am Heart J, 178, 65-73. (Read full article)
    39. King JB, Shah RU, Bress AP, Nelson RE, Bellows BK (2016). Cost-Effectiveness of Sacubitril-Valsartan Combination Therapy Compared With Enalapril for the Treatment of Heart Failure With Reduced Ejection Fraction. JACC Heart Fail, 4(5), 392-402. (Read full article)
    40. Shah RU, de Lemos JA, Wang TY, Chen AY, Thomas L, Sutton NR, Fang JC, Scirica BM, Henry TD, Granger CB (2016). Post-Hospital Outcomes of Patients With Acute Myocardial Infarction With Cardiogenic Shock: Findings From the NCDR. J Am Coll Cardiol, 67(7), 739-47. (Read full article)
    41. Shah RU, Rupp AB, Mowery D, Zhang M, Stoddard G, Deshmukh V, Bray BE, Hess R, Rondina MT (2016). Changes in Oral Anticoagulant Treatment Rates in Atrial Fibrillation before and after the Introduction of Direct Oral Anticoagulants. Neuroepidemiology, 47(3-4), 201-209. (Read full article)
    42. Pepine CJ, Ferdinand KC, Shaw LJ, Light-McGroary KA, Shah RU, Gulati M, Duvernoy C, Walsh MN, Bairey Merz CN, ACC CVD in Women Committee (2015). Emergence of Nonobstructive Coronary Artery Disease: A Woman's Problem and Need for Change in Definition on Angiography. J Am Coll Cardiol, 66(17), 1918-33. (Read full article)
    43. Shah RU, Henry TD, Rutten-Ramos S, Garberich RF, Tighiouart M, Bairey Merz CN (2015). Increasing percutaneous coronary interventions for ST-segment elevation myocardial infarction in the United States: progress and opportunity. JACC Cardiovasc Interv, 8(1 Pt B), 139-146. (Read full article)
    44. Kazi DS, Garber AM, Shah RU, Dudley RA, Mell MW, Rhee C, Moshkevich S, Boothroyd DB, Owens DK, Hlatky MA (2014). Cost-effectiveness of genotype-guided and dual antiplatelet therapies in acute coronary syndrome. Ann Intern Med, 160(4), 221-32. (Read full article)
    45. Simons CT, Cipriano LE, Shah RU, Garber AM, Owens DK, Hlatky MA (2013). Transcatheter aortic valve replacement in nonsurgical candidates with severe, symptomatic aortic stenosis: a cost-effectiveness analysis. Circ Cardiovasc Qual Outcomes, 6(4), 419-28. (Read full article)
    46. Shah RU, Chang TI, Fonarow GC (2013). Comparative effectiveness research in heart failure therapies: women, elderly patients, and patients with kidney disease. Heart Fail Clin, 9(1), 79-92. (Read full article)
    47. Shah RU, Freeman JV, Shilane D, Wang PJ, Go AS, Hlatky MA (2012). Procedural complications, rehospitalizations, and repeat procedures after catheter ablation for atrial fibrillation. J Am Coll Cardiol, 59(2), 143-9. (Read full article)
    48. Shah RU, Winkleby MA, Van Horn L, Phillips LS, Eaton CB, Martin LW, Rosal MC, Manson JE, Ning H, Lloyd-Jones DM, Klein L (2011). Education, income, and incident heart failure in post-menopausal women: the Women's Health Initiative Hormone Therapy Trials. J Am Coll Cardiol, 58(14), 1457-64. (Read full article)
    49. Shah RU, Tsai V, Klein L, Heidenreich PA (2011). Characteristics and outcomes of very elderly patients after first hospitalization for heart failure. Circ Heart Fail, 4(3), 301-7. (Read full article)

    Review

    1. Johnson AE, Brewer LC, Echols MR, Mazimba S, Shah RU, Breathett K (2022). Utilizing Artificial Intelligence to Enhance Health Equity Among Patients with Heart Failure. [Review]. Heart Fail Clin, 18(2), 259-273. (Read full article)
    2. Aggarwal N, Ahmed M, Basu S, Curtin JJ, Evans BJ, Matheny ME, Nundy S, Sendak MP, Shachar C, Shah RU, Thadaney-Israni S (2020). Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic. [Review]. NAM Perspect, 2020. (Read full article)
    3. AlBadri A, Wei J, Mehta PK, Shah R, Herscovici R, Gulati M, Shufelt C, Bairey Merz N (2017). Sex differences in coronary heart disease risk factors: rename it ischaemic heart disease! [Review]. Heart, 103(20), 1567-1568.
    4. Shah RU, Klein L, Lloyd-Jones DM (2009). Heart failure in women: epidemiology, biology and treatment. [Review]. Womens Health (Lond), 5(5), 517-27. (Read full article)

    Book Chapter

    1. Shah RU, Lloyd-Jones DM (2013). Heart Failure. In M. Goldman & R. Troisi (Eds.), Women & Health (2nd Edition). Academic Press.

    Editorial

    1. Shah RU, Bress AP, Vickers AJ (2022). Do Prediction Models Do More Harm Than Good? Circ Cardiovasc Qual Outcomes, 15(4), e008667. (Read full article)
    2. Rumsfeld JS, Shah RU (2019). Roadmap for the Digital Transformation of Healthcare: Lead, Facilitate and Partner https://www.medaxiom.com/blog/roadmap-for-the-digital-transformation-of-healthcare-lead-facilitate-and-partner/.
    3. Wang L, Selzman KA, Shah RU (2019). Peri-procedural complications in women: an alarming and consistent trend. 40(36), 3044-3045.
    4. Shah RU, Matheny ME (2018). Data and Information in the Sea of Electronic Health Records. 11(12), e005247.
    5. Shah RU, Rumsfeld JS (2017). Big Data in Cardiology. 38(24), 1865-1867.
    6. Shah RU, Merz CNB (2015). Publicly Available Data: Crowd Sourcing to Identify and Reduce Disparities. J Am Coll Cardiol, 66(18), 1973-1975. (Read full article)

    Letter

    1. Zheutlin AR, Caldwell DJ, Al Danaf J, Shah RU (2021). Prevalence of control groups in cardiovascular clinical trials: An analysis of ClinicalTrials.gov from 2009 through 2019. [Letter to the editor]. Am Heart J, 234, 133-135. (Read full article)
    2. Yin MY, Tandar A, Sharma V, Glotzbach JP, Shah RU, Dranow E, Tseliou E, Fang JC, Drakos SG, Welt FGP (2019). Left Ventricular Hemodynamic Changes During Transcatheter Aortic Valve Replacement Assessed by Real-Time Pressure-Volume Loops. [Letter to the editor]. JACC Cardiovasc Interv, 13(18), 2190-2192. (Read full article)
    3. Abedin Z, Hoerner R, Habboushe J, Lu Y, Kawamoto K, Warner PB, Shields DE, Shah RU (2020). Implementation of a Fast Healthcare Interoperability Resources-Based Clinical Decision Support Tool for Calculating CHA2DS2-VASc Scores. [Letter to the editor]. Circ Cardiovasc Qual Outcomes, 13(2), e006286. (Read full article)
    4. Shah RU, Stehlik J, Drakos SG, Fang JC (2015). Administrative data: proceed with caution. [Letter to the editor]. J Am Coll Cardiol, 65(10), 1063. (Read full article)

    Abstract

    1. Turner JL, Hardisty BE, Kaur G, Shah RU, Chelu MG, Han FT, Marrouche NF, Steinberg BA (04/06/2018). Accuracy of Patient Identification of Atrial Fibrillation in the Clinic Setting [Abstract]. Circulation: Cardiovascular Quality and Outcomes, 11(Suppl 1).
    2. Taggart M, Chapman WW, Steinberg BA, Ruckel S, Pregenzer-Wenzler A, Du Y, Ferraro J, Bucher BT, Lloyd-Jones DM, Rondina MT, Shah RU (4/6/2018). Development and Comparison of Two Natural Language Processing Methods for Identifying Bleeding Events in Clinical Text [Abstract]. Circulation: Cardiovascular Quality and Outcomes, 11(Suppl 1).
    3. Migotsky S, Kazi DS, Spivak ES, Shah SU, Shah RU (4/6/2018). Age-Related Practice and Outcome Patterns in Infective Endocarditis in the National Readmissions Database, 2010-2015 [Abstract]. Circulation: Cardiovascular Quality and Outcomes, 11(Suppl 1).
    4. Shah RU, Shao Y, Doing-Harris K, Weir C, Cheng Y, Bray B, Zeng Q (3/9/2018). Frailty and Cardiovascular Surgery, Deep Neural Network versus Support Vector Machine to Predict Death [Abstract]. Journal of the American College of Cardiology, 71(11), A1357.

    Other

    1. Reimer JR, Ahmed SM, Brintz B, Shah RU, Keegan LT, Ferrari MJ, Leung DT (2020). Modeling reductions in SARS-CoV-2 transmission and hospital burden achieved by prioritizing testing using a clinical prediction rule. (https://doi.org/10.1101/2020.07.07.20148510).

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