Daniel C Sullivan
Daniel C Sullivan
Professor, Radiology, Duke university
Verified email at duke.edu
Cited by
Cited by
The national lung screening trial: overview and study design
National Lung Screening Trial Research Team
Radiology 258 (1), 243-253, 2011
Job displacement and mortality: an analysis using administrative data
D Sullivan, T Von Wachter
The Quarterly Journal of Economics 124 (3), 1265-1306, 2009
Consensus recommendations for the use of 18F-FDG PET as an indicator of therapeutic response in patients in National Cancer Institute Trials
LK Shankar, JM Hoffman, S Bacharach, MM Graham, J Karp, ...
Journal of Nuclear Medicine 47 (6), 1059-1066, 2006
Progress and promise of FDG-PET imaging for cancer patient management and oncologic drug development
GJ Kelloff, JM Hoffman, B Johnson, HI Scher, BA Siegel, EY Cheng, ...
Clinical Cancer Research 11 (8), 2785-2808, 2005
American Cancer Society lung cancer screening guidelines
R Wender, ETH Fontham, E Barrera Jr, GA Colditz, TR Church, ...
CA: a cancer journal for clinicians 63 (2), 106-117, 2013
BI-RADS categorization as a predictor of malignancy
SG Orel, N Kay, C Reynolds, DC Sullivan
Radiology 211 (3), 845-850, 1999
Imaging biomarker roadmap for cancer studies
JPB O'Connor, EO Aboagye, JE Adams, HJWL Aerts, SF Barrington, ...
Nature reviews Clinical oncology 14 (3), 169, 2017
Variability in the interpretation of screening mammograms by US radiologists: findings from a national sample
CA Beam, PM Layde, DC Sullivan
Archives of internal medicine 156 (2), 209-213, 1996
MR imaging of ductal carcinoma in situ.
SG Orel, MH Mendonca, C Reynolds, MD Schnall, LJ Solin, DC Sullivan
Radiology 202 (2), 413-420, 1997
The progress and promise of molecular imaging probes in oncologic drug development
GJ Kelloff, KA Krohn, SM Larson, R Weissleder, DA Mankoff, JM Hoffman, ...
Clinical Cancer Research 11 (22), 7967-7985, 2005
Metrology standards for quantitative imaging biomarkers
DC Sullivan, NA Obuchowski, LG Kessler, DL Raunig, C Gatsonis, ...
Radiology 277 (3), 813-825, 2015
How experience and training influence mammography expertise
CF Nodine, HL Kundel, C Mello-Thoms, SP Weinstein, SG Orel, ...
Academic radiology 6 (10), 575-585, 1999
Prediction of breast cancer malignancy using an artificial neural network
CE Floyd Jr, JY Lo, AJ Yun, DC Sullivan, PJ Kornguth
Cancer: Interdisciplinary International Journal of the American Cancer …, 1994
National Institutes of Health Consensus Development Conference statement: breast cancer screening for women ages 40–49, January 21–23, 1997
National Institutes of Health Consensus Development Panel
Journal of the National Cancer Institute 89 (14), 960-965, 1997
Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment
DL Raunig, LM McShane, G Pennello, C Gatsonis, PL Carson, ...
Statistical methods in medical research 24 (1), 27-67, 2015
The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions
LG Kessler, HX Barnhart, AJ Buckler, KR Choudhury, MV Kondratovich, ...
Statistical methods in medical research 24 (1), 9-26, 2015
Monopsony power in the market for nurses
D Sullivan
The Journal of Law and Economics 32 (2, Part 2), S135-S178, 1989
Diagnostic performance characteristics of architectural features revealed by high spatial-resolution MR imaging of the breast.
LW Nunes, MD Schnall, ES Siegelman, CP Langlotz, SG Orel, D Sullivan, ...
AJR. American journal of roentgenology 169 (2), 409-415, 1997
Assessing relationships among strategic types, distinctive marketing competencies, and organizational performance
AG Woodside, DP Sullivan, RJ Trappey III
Journal of Business research 45 (2), 135-146, 1999
Breast tissue density quantification via digitized mammograms
PK Saha, JK Udupa, EF Conant, DP Chakraborty, D Sullivan
IEEE transactions on medical imaging 20 (8), 792-803, 2001
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