Michael J Pencina, PhD
Adjunct Professor
Boston University School of Public Health
Biostatistics

PhD, Boston University
MA, University of Warsaw



Dr. Michael Pencina is the Duke Clinical Research Institute Director of Biostatistics. He is Professor of Biostatistics & Bioinformatics at Duke and Adjunct Professor in the Department of Biostatistics at Boston University.

As the DCRI Director of Biostatistics, Dr. Pencina serves as a key institutional leader overseeing the strategic and operational direction of our biostatistics talent and resources at the DCRI. In this role, Dr. Pencina guides a strategic vision to meet the needs of DCRI investigators by developing necessary infrastructure while also partnering with the Biostatistics & Bioinformatics Department to assure that the DCRI’s objectives and services are well understood and supported.

Prior to joining the DCRI in 2013, Dr. Pencina served as an associate professor in the Department of Biostatistics at Boston University and as Director of Statistical Consulting at the Harvard Clinical Research Institute. He brings a wealth of experience in both clinical trials and observational analyses. He has worked on a number of large clinical trials as well as Framingham Heart Study projects. Dr. Pencina is an expert in cardiovascular disease risk prediction model development and assessment of performance. The novel metrics (net reclassification improvement and integrated discrimination improvement) for the assessment of usefulness of new biomarkers and genetic factors in risk prediction proposed by Dr. Pencina have been incorporated into the reporting guidelines. For the past year, Dr. Pencina has also served as the Associate Editor for Statistics in Medicine. He has authored more than 150 manuscripts that have been published in peer-reviewed journals. Dr. Pencina earned his PhD in Mathematics and Statistics at Boston University.

Member
Boston University
Evans Center for Interdisciplinary Biomedical Research


Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

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  1. Pencina MJ, McCall J, Economou-Zavlanos NJ. A Federated Registration System for Artificial Intelligence in Health. JAMA. 2024 Sep 10; 332(10):789-790. PMID: 39133500
     
  2. Hao S, Matos J, Dempsey K, Alwakeel M, Houghtaling J, Hong C, Gichoya J, Kibbe W, Pencina M, Cox CE, Ian Wong A. ENCoDE - a skin tone and clinical dataset from a prospective trial on acute care patients. medRxiv. 2024 Aug 08. PMID: 39211868; PMCID: PMC11361235; DOI: 10.1101/2024.08.07.24311623;
     
  3. Kohli-Lynch C, Thanassoulis G, Pencina M, Sehayek D, Pencina K, Moran A, Sniderman AD. Reply: Origins and Previous Applications of Causal-Benefit Models. JACC Adv. 2024 Sep; 3(9):101090. PMID: 39165836; PMCID: PMC11334702; DOI: 10.1016/j.jacadv.2024.101090;
     
  4. Cary MP, Bessias S, McCall J, Pencina MJ, Grady SD, Lytle K, Economou-Zavlanos NJ. Empowering nurses to champion Health equity & BE FAIR: Bias elimination for fair and responsible AI in healthcare. J Nurs Scholarsh. 2024 Jul 29. PMID: 39075715
     
  5. Sniderman AD, Dufresne L, Pencina KM, Bilgic S, Thanassoulis G, Pencina MJ. Discordance among apoB, non-high-density lipoprotein cholesterol, and triglycerides: implications for cardiovascular prevention. Eur Heart J. 2024 Jul 12; 45(27):2410-2418. PMID: 38700053; PMCID: PMC11242442; DOI: 10.1093/eurheartj/ehae258;
     
  6. Hickey J, Henao R, Wojdyla D, Pencina M, Engelhard M. Adaptive Discretization for Event PredicTion (ADEPT). Proc Mach Learn Res. 2024 May; 238:1351-1359. PMID: 38725587; PMCID: PMC11078624
     
  7. D'Agostino McGowan L, Pencina M, Sullivan L, D'Agostino RB. In Memoriam: Ralph B. D'Agostino, Sr. (1940-2023). Am J Epidemiol. 2024 Mar 06.View Related Profiles. PMID: 38451245
     
  8. Economou-Zavlanos NJ, Bessias S, Cary MP, Bedoya AD, Goldstein BA, Jelovsek JE, O'Brien CL, Walden N, Elmore M, Parrish AB, Elengold S, Lytle KS, Balu S, Lipkin ME, Shariff AI, Gao M, Leverenz D, Henao R, Ming DY, Gallagher DM, Pencina MJ, Poon EG. Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare. J Am Med Inform Assoc. 2024 Feb 16; 31(3):705-713. PMID: 38031481; PMCID: PMC10873841; DOI: 10.1093/jamia/ocad221;
     
  9. Kohli-Lynch C, Thanassoulis G, Pencina M, Sehayek D, Pencina K, Moran A, Sniderman AD. The Causal-Benefit Model to Prevent Cardiovascular Events. JACC Adv. 2024 Mar; 3(3):100825. PMID: 38938840; PMCID: PMC11198721; DOI: 10.1016/j.jacadv.2023.100825;
     
  10. Shah NH, Halamka JD, Saria S, Pencina M, Tazbaz T, Tripathi M, Callahan A, Hildahl H, Anderson B. A Nationwide Network of Health AI Assurance Laboratories. JAMA. 2024 Jan 16; 331(3):245-249. PMID: 38117493
     
Showing 10 of 415 results. Show More

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 414 publications over 21 distinct years, with a maximum of 35 publications in 2013

YearPublications
20042
20058
20067
200713
200824
200916
201026
201132
201230
201335
201434
201531
201634
201721
201811
201921
202017
202111
202211
202320
202410

In addition to these self-described keywords below, a list of MeSH based concepts is available here.

cardiovascular disease risk prediction model development
statistics in medicine
data science
machine learning
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801 Massachusetts Ave Crosstown Center
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