Big Heart Data: Advancing Health Informatics Through Data Sharing in Cardiovascular Imaging
Open accessAbstract
The burden of heart disease is rapidly worsening due to the increasing prevalence of obesity and diabetes. Data sharing and open database resources for heart health informatics are important for advancing our understanding of cardiovascular function, disease progression and therapeutics. Data sharing enables valuable information, often obtained at considerable expense and effort, to be reused beyond the specific objectives of the original study. Many government funding agencies and journal publishers are requiring data reuse, and are providing mechanisms for data curation and archival. Tools and infrastructure are available to archive anonymous data from a wide range of studies, from descriptive epidemiological data to gigabytes of imaging data. Meta-analyses can be performed to combine raw data from disparate studies to obtain unique comparisons or to enhance statistical power. Open benchmark datasets are invaluable for validating data analysis algorithms and objectively comparing results. This review provides a rationale for increased data sharing and surveys recent progress in the cardiovascular domain. We also highlight the potential of recent large cardiovascular epidemiological studies enabling collaborative efforts to facilitate data sharing, algorithms benchmarking, disease modeling and statistical atlases.
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Multi-institutional collaboration is becoming the vehicle driving the creation of well-curated and semantically annotated large cohorts enhanced with research methods and results metadata, underpinning reproducible, extensible, and explainable research.
“Toward this direction, multi-institutional collaboration is quickly becoming the vehicle driving the creation of well-curated and semantically annotated large cohorts that are further enhanced with research methods and results metadata, underpinning reproducible, extensible, and explainable research [59], [60].”
From AI in Medical Imaging Informatics: Current Challenges and Future Directions (2020) · cites this paper as [60]
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Goldberger, A. L., Amaral, L. A. N., Glass, L., Hausdorff, J. M., Ivanov, P. C., Mark, R. G., Mietus, J. E., Moody, G. B., Peng, C.-K., & Stanley, H. E. (2000) · Circulation · doi:10.1161/01.cir.101.23.e215 · Cited by 14,809 · see citing works
Ahmed, A., Jorna, T., & Bhandari, S. (2016) · The Nephron journals/Nephron journals · doi:10.1159/000447068 · Cited by 11,782 · see citing works
Murray, C. J. L., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., Ezzati, M., Shibuya, K., Salomon, J. A., Abdalla, S., et al. (2012) · The Lancet · doi:10.1016/s0140-6736(12)61689-4 · Cited by 8,888 · see citing works
Multi-Ethnic Study of Atherosclerosis: Objectives and Design
Bild, D. E. (2002) · American Journal of Epidemiology · doi:10.1093/aje/kwf113 · Cited by 3,942 · see citing works
Cohn, J. N., Ferrari, R., & Sharpe, N. (2000) · Journal of the American College of Cardiology · doi:10.1016/s0735-1097(99)00630-0 · Cited by 2,591 · see citing works
KANNEL, W. B., DAWBER, T. R., KAGAN, A., REVOTSKIE, N., & STOKES, J. (1961) · Annals of Internal Medicine · doi:10.7326/0003-4819-55-1-33 · Cited by 1,837 · see citing works
Left Ventricular Remodeling After Myocardial Infarction
Sutton, M. G. S. J., & Sharpe, N. (2000) · Circulation · doi:10.1161/01.cir.101.25.2981 · Cited by 1,827 · see citing works
The Inevitable Application of Big Data to Health Care
Murdoch, T. B., & Detsky, A. S. (2013) · JAMA · doi:10.1001/jama.2013.393 · Cited by 1,676 · see citing works
The Relationship of Left Ventricular Mass and Geometry to Incident Cardiovascular Events
Bluemke, D. A., Kronmal, R. A., Lima, J. A. C., Liu, K., Olson, J., Burke, G. L., & Folsom, A. R. (2008) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2008.09.014 · Cited by 811 · see citing works
Left Ventricular Remodeling in Heart Failure
Konstam, M. A., Kramer, D. G., Patel, A. R., Maron, M. S., & Udelson, J. E. (2011) · JACC. Cardiovascular imaging · doi:10.1016/j.jcmg.2010.10.008 · Cited by 770 · see citing works
Pathological Ventricular Remodeling
Burchfield, J. S., Xie, M., & Hill, J. A. (2013) · Circulation · doi:10.1161/circulationaha.113.001878 · Cited by 768 · see citing works
Epidemiological studies of CHD and the evolution of preventive cardiology
Wong, N. D. (2014) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2014.26 · Cited by 664 · see citing works
Taylor, H. A., WILSON, J. G., Jones, D. W., Sarpong, D. F., Srinivasan, A., Garrison, R. J., Nelson, C. R., & Wyatt, S. B. (2005) · PubMed · Cited by 525 · see citing works
Lewandowski, A. J., Augustine, D. X., Lamata, P., Davis, E., Lazdam, M., Francis, J. M., McCormick, K. P., Wilkinson, A. R., Singhal, A., Lucas, A., et al. (2012) · Circulation · doi:10.1161/circulationaha.112.126920 · Cited by 469 · see citing works
Vasan, R. S., Larson, M. G., Benjamin, E. J., Evans, J. C., & Levy, D. (1997) · New England Journal of Medicine · doi:10.1056/nejm199705083361903 · Cited by 402 · see citing works
Schaap, M., Metz, C., van Walsum, T., van der Giessen, A. G., Weustink, A. C., Mollet, N. R., Bauer, C., Bogunović, H., Castro‐González, C., Deng, X. B., et al. (2009) · Medical Image Analysis · doi:10.1016/j.media.2009.06.003 · Cited by 364 · see citing works
Schelbert, E. B., Cao, J. J., Sigurdsson, S. O., Aspelund, T., Kellman, P., Aletras, A. H., Dyke, C. K., Þorgeirsson, G., Eiríksdóttir, G., Launer, L. J., et al. (2012) · JAMA · doi:10.1001/2012.jama.11089 · Cited by 284 · see citing works
Fonseca, C. G., Backhaus, M., Bluemke, D. A., Britten, R. D., Chung, J. D., Cowan, B. R., Dinov, I. D., Finn, J. P., Hunter, P. J., Kadish, A. H., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr360 · Cited by 281 · see citing works
Self-citationBruder, O., Wagner, A., Lombardi, M., et al. (2013) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-15-9 · Cited by 278 · see citing works
Mitchell, G. F., Lamas, G. A., Vaughan, D. E., & Pfeffer, M. A. (1992) · Journal of the American College of Cardiology · doi:10.1016/0735-1097(92)90314-d · Cited by 273 · see citing works
Petersen, S. E., Matthews, P. M., Bamberg, F., Bluemke, D. A., Francis, J. M., Friedrich, M. G., Leeson, P., Nagel, E. C., Plein, S., Rademakers, F. E., et al. (2013) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-15-46 · Cited by 266 · see citing works
Self-citationACC/AHA/HRS 2006 Key Data Elements and Definitions for Electrophysiological Studies and Procedures
Buxton, A. E., Calkins, H. G., Callans, D. J., Dimarco, J., Fisher, J. D., Greene, H. L., Haines, D. E., Hayes, D. L., Heidenreich, P. A., Miller, J. M., et al. (2006) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2006.09.020 · Cited by 237 · see citing works
Maxime Sermesant, B., Chabiniok, R., Chinchapatnam, P. P., Mansi, T., Billet, F., Moireau, P., Peyrat, J., Wong, K. C. L., Relan, J., Rhode, K., et al. (2011) · Medical Image Analysis · doi:10.1016/j.media.2011.07.003 · Cited by 232 · see citing works
Human Atlas of the Cardiac Fiber Architecture: Study on a Healthy Population
Lombaert, H., Peyrat, J., Croisille, P., Rapacchi, S., Fanton, L., Farida Cheriet, A., Clarysse, P., Magnin, I. E., Delingette, H., & Ayache, N. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2192743 · Cited by 227 · see citing works
Suinesiaputra, A., Cowan, B. R., Al‐Agamy, A. O., Elattar, M., Ayache, N., Fahmy, A. S., Khalifa, A. M., Medrano−Gracia, P., Jolly, M., Kadish, A. H., et al. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.09.001 · Cited by 206 · see citing works
Self-citationPublishing data from electronic health records while preserving privacy: A survey of algorithms
Gkoulalas-Divanis, A., Loukides, G., & Sun, J. (2014) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.06.002 · Cited by 203 · see citing works
The Jackson Heart Study: an overview.
Taylor, H. A. (2005) · PubMed · Cited by 182 · see citing works
Mannaerts, H. F. J. (2004) · European Heart Journal · doi:10.1016/j.ehj.2004.02.030 · Cited by 179 · see citing works
Karim, R., Housden, R. J., Balasubramaniam, M., Chen, Z., Perry, D. J., Uddin, A., Al-Beyatti, Y., Palkhi, E., Acheampong, P., Obom, S., et al. (2013) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-15-105 · Cited by 171 · see citing works
Benchmarking framework for myocardial tracking and deformation algorithms: An open access database
Tobon‐Gomez, C., Craene, M. D., McLeod, K., Tautz, L., Shi, W., Hennemuth, A., Prakosa, A., Wang, H., Carr‐White, G., Kapetanakis, S., et al. (2013) · Medical Image Analysis · doi:10.1016/j.media.2013.03.008 · Cited by 171 · see citing works
ACC/AHA/HRS 2006 Key Data Elements and Definitions for Electrophysiological Studies and Procedures
Buxton, A. E., Calkins, H., Callans, D. J., Dimarco, J., Fisher, J. D., Greene, H. L., Haines, D. E., Haines, D. E., Heidenreich, P. A., Miller, J. M., et al. (2006) · Circulation · doi:10.1161/circulationaha.106.180199 · Cited by 164 · see citing works
iDASH: integrating data for analysis, anonymization, and sharing
Lucila Ohno-machado, A., Bafna, V., Boxwala, A. A., Chapman, B. E., Chapman, W. W., Chaudhuri, K., Day, M. E., Farcas, C., Heintzman, N. D., Jiang, X., et al. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000538 · Cited by 148 · see citing works
Lauer, M. S., Evans, J. C., & Levy, D. A. (1992) · The American Journal of Cardiology · doi:10.1016/0002-9149(92)90052-z · Cited by 141 · see citing works
Computational cardiac atlases: from patient to population and back
Young, A. A., & Frangi, A. F. (2008) · Experimental Physiology · doi:10.1113/expphysiol.2008.044081 · Cited by 138 · see citing works
Self-citationLeft ventricular hypertrophy and risk of cardiac failure: insights from the Framingham Study.
Kannel, W. B., Levy, D. A., & Cupples, L. A. (1987) · PubMed · Cited by 131 · see citing works
euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling
Smith, N. P., de Vecchi, A., McCormick, M., Nordsletten, D., Cámara, Ó., Frangi, A. F., Delingette, H., Maxime Sermesant, B., Relan, J., Ayache, N., et al. (2011) · Interface Focus · doi:10.1098/rsfs.2010.0048 · Cited by 128 · see citing works
Kadish, A. H., Bello, D. B., Finn, J. P., Bonow, R. O., Schaechter, A., Subacius, H. P., Albert, C. M., Daubert, J. P., Fonseca, C. G., & Goldberger, J. J. (2009) · Journal of Cardiovascular Electrophysiology · doi:10.1111/j.1540-8167.2009.01503.x · Cited by 118 · see citing works
A Virtual Imaging Platform for Multi-Modality Medical Image Simulation
Glatard, T., Lartizien, C., Gibaud, B., et al. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2220154 · Cited by 112 · see citing works
Sociocultural methods in the Jackson Heart Study: conceptual and descriptive overview.
Payne, T. J., Wyatt, S. B., Mosley, T. H., Dubbert, P. M., Guiterrez-Mohammed, M. L., Calvin, R. L., Taylor, H. A., & Williams, D. R. (2005) · PubMed · Cited by 109 · see citing works
An accurate, fast and robust method to generate patient-specific cubic Hermite meshes
Lamata, P., Niederer, S., Nordsletten, D., Barber, D. C., Roy, I., Hose, D. R., & Smith, N. P. (2011) · Medical Image Analysis · doi:10.1016/j.media.2011.06.010 · Cited by 104 · see citing works
Medrano-Gracia, P., Cowan, B. R., Ambale-Venkatesh, B., Bluemke, D. A., Eng, J., Finn, J. P., Fonseca, C. G., Lima, J. A., Suinesiaputra, A., & Young, A. A. (2014) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/s12968-014-0056-2 · Cited by 98 · see citing works
Self-citationA High-Resolution Atlas and Statistical Model of the Human Heart From Multislice CT
Hoogendoorn, C., Duchateau, N., Sánchez‐Quintana, D., Whitmarsh, T., Sukno, F. M., Craene, M. D., Lekadir, K., & Frangi, A. F. (2012) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2012.2230015 · Cited by 91 · see citing works
Clark, C. R., Ommerborn, M. J., Hickson, D. A., Grooms, K. N., Sims, M., Taylor, H. A., & Albert, M. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063254 · Cited by 90 · see citing works
Left Ventricular Hypertrophy and Risk of Cardiac Failure
Kannel, W. B., Levy, D. A., & Cupples, L. A. (1987) · Journal of Cardiovascular Pharmacology · doi:10.1097/00005344-198700106-00018 · Cited by 86 · see citing works
Suinesiaputra, A., Frangi, A. F., Kaandorp, T. A. M., Lamb, H. J., Bax, J. J., Reiber, J. H. C., & Lelieveldt, B. P. F. (2009) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2008966 · Cited by 84 · see citing works
Self-citationRelation of left ventricular sphericity to 10-year survival after acute myocardial infarction
Wong, S. P., French, J. K., Lydon, A., Manda, S., Gao, W., Ashton, N. G., & White, H. D. (2004) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2004.07.110 · Cited by 77 · see citing works
Borugian, M. J., Robson, P. J., Fortier, I., Parker, L., McLaughlin, J. R., Knoppers, B. M., Bedard, K., Gallagher, R. P., Sinclair, S., Ferretti, V., et al. (2010) · Canadian Medical Association Journal · doi:10.1503/cmaj.091540 · Cited by 73 · see citing works
Duchateau, N., Craene, M. D., Piella, G., Silva, E., Doltra, A., Sitges, M., Bijnens, B. H., & Frangi, A. F. (2011) · Medical Image Analysis · doi:10.1016/j.media.2010.12.006 · Cited by 71 · see citing works
GigaDB: announcing the GigaScience database
Sneddon, T. P., Li, P., & Edmunds, S. (2012) · GigaScience · doi:10.1186/2047-217x-1-11 · Cited by 71 · see citing works
An automatic service for the personalization of ventricular cardiac meshes
Lamata, P., Sinclair, M., Kerfoot, E., Lee, A., Crozier, A., Blazevic, B., Land, S., Lewandowski, A. J., Barber, D. C., Niederer, S., et al. (2013) · Journal of The Royal Society Interface · doi:10.1098/rsif.2013.1023 · Cited by 60 · see citing works
Chuang, M. L., Gona, P. N., Hautvast, G. L. T. F., Salton, C. J., Breeuwer, M. M., O’Donnell, C. J., & Manning, W. J. (2013) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.24239 · Cited by 59 · see citing works
A review of ECG storage formats
Bond, R., Finlay, D., Nugent, C., et al. (2011) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2011.06.008 · Cited by 54 · see citing works
Left Ventricular Segmentation Challenge from Cardiac MRI: A Collation Study
Suinesiaputra, A., Cowan, B. R., Finn, J. P., et al. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-28326-0_9 · Cited by 51 · see citing works
Self-citationMori, S., Oishi, K., Faria, A. V., & Miller, M. I. (2013) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-071812-152335 · Cited by 47 · see citing works
Patient-controlled sharing of medical imaging data across unaffiliated healthcare organizations
Ge, Y., Ahn, D. K., Unde, B., Gage, H. D., & Carr, J. J. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2012-001146 · Cited by 43 · see citing works
Novel Biomarkers in Cardiovascular Disease
Stratz, C., Amann, M., Berg, D. D., Morrow, D. A., Neumann, F., & Hochholzer, W. (2012) · Cardiology in Review · doi:10.1097/crd.0b013e31824394e1 · Cited by 40 · see citing works
How to detect disease progression in pulmonary arterial hypertension
Vachiéry, J., Yerly, P., & Huez, S. (2012) · European Respiratory Review · doi:10.1183/09059180.00009011 · Cited by 40 · see citing works
The twin questions of personalized medicine: who are you and whom do you most resemble?
Kohane, I. S. (2009) · Genome Medicine · doi:10.1186/gm4 · Cited by 38 · see citing works
FieldML, a proposed open standard for the Physiome project for mathematical model representation
Britten, R. D., Christie, G. R., Little, C., Miller, A. K., Bradley, C. P., Wu, A., Yu, T., Hunter, P. J., & Nielsen, P. F. (2013) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-013-1097-7 · Cited by 36 · see citing works
Medical Image and Data Sharing: Are We There Yet?
Flanders, A. E. (2009) · Radiographics · doi:10.1148/rg.295095151 · Cited by 34 · see citing works
Towards personalized clinical in-silico modeling of atrial anatomy and electrophysiology
Krueger, M. W., Schulze, W. H. W., Rhode, K., Razavi, R., Seemann, G., & Dössel, O. (2012) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-012-0970-0 · Cited by 34 · see citing works
Bild, D. E., McClelland, R. L., Kaufman, J. D., Blumenthal, R. S., Burke, G. L., Carr, J. J., Post, W. S., Register, T. C., Shea, S., & Szklo, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0094916 · Cited by 33 · see citing works
Predict, prevent and personalize: Genomic and proteomic approaches to cardiovascular medicine
Ouzounian, M., Lee, D. S., Gramolini, A. O., Emili, A., Fukuoka, M., & Liu, P. P. (2007) · Canadian Journal of Cardiology · doi:10.1016/s0828-282x(07)71003-6 · Cited by 32 · see citing works
Medrano−Gracia, P., Cowan, B. R., Bluemke, D. A., Finn, J. P., Kadish, A. H., Lee, D. C., Lima, J. A. C., Suinesiaputra, A., & Young, A. A. (2013) · Journal of Cardiovascular Magnetic Resonance · doi:10.1186/1532-429x-15-80 · Cited by 32 · see citing works
Self-citationGianni, D., McKeever, S., Yu, T., Britten, R. D., Delingette, H., Frangi, A. F., Hunter, P. J., & Smith, N. P. (2010) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2010.0025 · Cited by 29 · see citing works
Treatment of Hypertension Among A frican A mericans: The J ackson Heart Study
Harman, J. L., Walker, E., Charbonneau, V., et al. (2013) · Journal of Clinical Hypertension · doi:10.1111/jch.12088 · Cited by 28 · see citing works
Statistical Personalization of Ventricular Fiber Orientation Using Shape Predictors
Lekadir, K., Hoogendoorn, C., Pereañez, M., et al. (2014) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2013.2297333 · Cited by 24 · see citing works
Weese, J., Groth, A., Nickisch, H., Barschdorf, H., Weber, F. M., Velut, J., Castro, M., Toumoulin, C., Coatrieux, J.-L., Craene, M. D., et al. (2013) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-012-1027-0 · Cited by 22 · see citing works
Individualized Cardiovascular Risk Assessment By Cardiovascular Magnetic Resonance
Hinojar, R., Botnar, R. M., Kaski, J. C., Prasad, S. K., Nagel, E. C., & Püntmann, V. O. (2014) · Future Cardiology · doi:10.2217/fca.13.102 · Cited by 21 · see citing works
Kerfoot, E., Lamata, P., Niederer, S., Hose, R., Spaan, J. A. E., & Smith, N. P. (2013) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-012-1023-4 · Cited by 20 · see citing works
De-identification of clinical narratives through writing complexity measures
Li, M., Carrell, D., Aberdeen, J. S., Hirschman, L., & Malin, B. (2014) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2014.07.002 · Cited by 19 · see citing works
Welter, P., Hocken, C., Deserno, T. M., et al. (2010) · International Journal of Computer Assisted Radiology and Surgery · doi:10.1007/s11548-010-0416-9 · Cited by 16 · see citing works
Prevention and reversal of left ventricular remodeling: Summation
Konstam, M. A., Udelson, J. E., & Sharpe, N. (2002) · Journal of Cardiac Failure · doi:10.1054/jcaf.2002.130303 · Cited by 11 · see citing works
McLeod, K., Seiler, C., Maxime Sermesant, B., et al. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40763-5_62 · Cited by 8 · see citing works
Ontological labels for automated location of anatomical shape differences
Steinert‐Threlkeld, S., Ardekani, S., Mejino, J. L. V., Detwiler, L. T., Brinkley, J. F., Halle, M., Kikinis, R., Winslow, R. L., Miller, M. I., & Ratnanather, J. T. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.02.013 · Cited by 7 · see citing works
Carr, J. J. (2012) · PubMed · Cited by 3 · see citing works
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AI in Medical Imaging Informatics: Current Challenges and Future Directions
Panayides, A. S., Amini, A., Filipovic, N. D., Sharma, A., Tsaftaris, S. A., Young, A., Foran, D., Do, N., Golemati, S., Kurc, T., et al. (2020) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2020.2991043 · Cited by 713 · see citing works
Self-citationBai, W., Shi, W., de Marvao, A., Dawes, T. J. W., O’Regan, D. P., Cook, S. A., & Rueckert, D. (2015) · Medical Image Analysis · doi:10.1016/j.media.2015.08.009 · Cited by 171 · see citing works
Statistical Shape Modeling of the Left Ventricle: Myocardial Infarct Classification Challenge
Suinesiaputra, A., Dhooge, J., Duchateau, N., Ehrhardt, J., Frangi, A. F., Gooya, A., Grau, V., Lekadir, K., Lu, A., Mukhopadhyay, A., et al. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2017.2652449 · Cited by 95 · see citing works
Self-citation
- Authors
- Suinesiaputra, A., Medrano-Gracia, P., Cowan, B. R., & Young, A. A.
- Affiliations
- University of Auckland (NZ)
- Venue
- IEEE Journal of Biomedical and Health Informatics
- Published
- 2015-07
- Volume
- 19
- Issue
- 4
- Pages
- 1283-1290
- ISSN
- 2168-2194 (ISSN-L)
- 2168-2208
- PMC
- PMC4659497
- OpenAlex
- W2071151688
- Cited by
- 45
- References
- 76
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 4 · 2020: 6 · 2019: 5 · 2018: 4 · 2017: 8 · 2016: 7 · 2015: 3
- FWCI
- 16.59
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- IEEE Journal of Biomedical and Health Informatics (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- ResearchSpace (University of Auckland) (submittedVersion, cc-by)
- Funders
- National Heart Lung and Blood Institute (R01HL087773)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Cardiac Imaging and Diagnostics
- Social Sciences › Sociology and Political Science › Data Analysis and Archiving
- Keywords
- data sharing, cardiovascular imaging, heart disease, open database, data reuse, data curation, data archiving, meta-analysis, benchmark dataset, algorithm validation, large-scale epidemiological studies, disease modeling, statistical atlas, obesity, diabetes mellitus
- MeSH terms
- Humans, Magnetic Resonance Imaging, Medical Informatics, Models, Cardiovascular, Databases, Factual, Internet, Information Dissemination, Cardiac Imaging Techniques
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Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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