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Daniel B. Mark
Researcher at Duke University
Publications - 605
Citations - 86108
Daniel B. Mark is an academic researcher from Duke University. The author has contributed to research in topics: Myocardial infarction & Coronary artery disease. The author has an hindex of 124, co-authored 576 publications receiving 78385 citations. Previous affiliations of Daniel B. Mark include Westchester Medical Center & University of Louisville.
Papers
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Journal ArticleDOI
Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
TL;DR: In this article, an easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, which are particularly needed for binary, ordinal, and time-to-event outcomes.
Journal ArticleDOI
Amiodarone or an implantable cardioverter-defibrillator for congestive Heart failure
Gust H. Bardy,Kerry L. Lee,Daniel B. Mark,Jeanne E. Poole,Douglas L. Packer,Robin Boineau,Michael J. Domanski,Charles Troutman,Jill Anderson,Steven McNulty,Nancy E. Clapp-Channing,Linda Davidson-Ray,Elizabeth S. Fraulo,Daniel P. Fishbein,Richard M. Luceri,John Ip +15 more
TL;DR: In patients with NYHA class II or III CHF and LVEF of 35 percent or less, amiodarone has no favorable effect on survival, whereas single-lead, shock-only ICD therapy reduces overall mortality by 23 percent.
Book ChapterDOI
Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors
TL;DR: An easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes.
Tutorial in biostatistics multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
Kerry L. Lee,Daniel B. Mark +1 more
TL;DR: An easily interpretable index of predictive discrimination as well as methods for assessing calibration of predicted survival probabilities are discussed, which are applicable to all regression models, but are particularly needed for binary, ordinal, and time-to-event outcomes.
Journal ArticleDOI
ACC/AHA 2002 Guideline Update for Exercise Testing: Summary Article A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee to Update the 1997 Exercise Testing Guidelines)
Raymond J. Gibbons,Gary J. Balady,J. Timothy Bricker,Bernard R. Chaitman,Gerald F. Fletcher,Victor F. Froelicher,Daniel B. Mark,Ben D. McCallister,Aryan N. Mooss,Michael G. O’Reilly,William L. Winters,Elliott M. Antman,Joseph S. Alpert,David P. Faxon,Valentin Fuster,Gabriel Gregoratos,Loren F. Hiratzka,Alice K. Jacobs,Richard O. Russell,Sidney C. Smith +19 more
TL;DR: The American College of Cardiology (ACC)/AHA Task Force on Practice Guidelines regularly reviews existing guidelines to determine when an update or full revision is needed.