Published on 22.08.14 in Vol 2, No 2 (2014): Jul-Dec
Works citing "Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference"
According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.3447):
(note that this is only a small subset of citations)
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Celi LA, Ippolito A, Montgomery RA, Moses C, Stone DJ. Crowdsourcing Knowledge Discovery and Innovations in Medicine. Journal of Medical Internet Research 2014;16(9):e216
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Sewerin P, Ostendorf B, Hueber AJ, Kleyer A. Big Data in der Bildgebung. Zeitschrift für Rheumatologie 2018;77(3):203
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Eytan D, Jegatheeswaran A, Mazwi ML, Assadi A, Goodwin AJ, Greer RW, Goodfellow SD, Laussen PC. Temporal Variability in the Sampling of Vital Sign Data Limits the Accuracy of Patient State Estimation*. Pediatric Critical Care Medicine 2019;20(7):e333
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Wellner B, Grand J, Canzone E, Coarr M, Brady PW, Simmons J, Kirkendall E, Dean N, Kleinman M, Sylvester P. Predicting Unplanned Transfers to the Intensive Care Unit: A Machine Learning Approach Leveraging Diverse Clinical Elements. JMIR Medical Informatics 2017;5(4):e45
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Huddar V, Desiraju BK, Rajan V, Bhattacharya S, Roy S, Reddy CK. Predicting Complications in Critical Care Using Heterogeneous Clinical Data. IEEE Access 2016;4:7988
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Ding R, Arighi CN, Lee J, Wu CH, Vijay-Shanker K, Wilbur WJ. pGenN, a Gene Normalization Tool for Plant Genes and Proteins in Scientific Literature. PLOS ONE 2015;10(8):e0135305
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Jaffee EM, Dang CV, Agus DB, Alexander BM, Anderson KC, Ashworth A, Barker AD, Bastani R, Bhatia S, Bluestone JA, Brawley O, Butte AJ, Coit DG, Davidson NE, Davis M, DePinho RA, Diasio RB, Draetta G, Frazier AL, Futreal A, Gambhir SS, Ganz PA, Garraway L, Gerson S, Gupta S, Heath J, Hoffman RI, Hudis C, Hughes-Halbert C, Ibrahim R, Jadvar H, Kavanagh B, Kittles R, Le Q, Lippman SM, Mankoff D, Mardis ER, Mayer DK, McMasters K, Meropol NJ, Mitchell B, Naredi P, Ornish D, Pawlik TM, Peppercorn J, Pomper MG, Raghavan D, Ritchie C, Schwarz SW, Sullivan R, Wahl R, Wolchok JD, Wong SL, Yung A. Future cancer research priorities in the USA: a Lancet Oncology Commission. The Lancet Oncology 2017;18(11):e653
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Tobore I, Li J, Yuhang L, Al-Handarish Y, Kandwal A, Nie Z, Wang L. Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations. JMIR mHealth and uHealth 2019;7(8):e11966
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Nepal S, Ranjan R, Choo KR. Trustworthy Processing of Healthcare Big Data in Hybrid Clouds. IEEE Cloud Computing 2015;2(2):78
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Ghassemi M, Celi LA, Stone DJ. State of the art review: the data revolution in critical care. Critical Care 2015;19(1)
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Kansagra AP, Yu JJ, Chatterjee AR, Lenchik L, Chow DS, Prater AB, Yeh J, Doshi AM, Hawkins CM, Heilbrun ME, Smith SE, Oselkin M, Gupta P, Ali S. Big Data and the Future of Radiology Informatics. Academic Radiology 2016;23(1):30
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Panch T, Szolovits P, Atun R. Artificial intelligence, machine learning and health systems. Journal of Global Health 2018;8(2)
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Moseley ET, Hsu DJ, Stone DJ, Celi LA. Beyond Open Big Data: Addressing Unreliable Research. Journal of Medical Internet Research 2014;16(11):e259
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Johnson AEW, Ghassemi MM, Nemati S, Niehaus KE, Clifton D, Clifford GD. Machine Learning and Decision Support in Critical Care. Proceedings of the IEEE 2016;104(2):444
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Eytan D, Goodwin AJ, Greer R, Guerguerian A, Mazwi M, Laussen PC. Distributions and Behavior of Vital Signs in Critically Ill Children by Admission Diagnosis*. Pediatric Critical Care Medicine 2018;19(2):115
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Štufi M, Bačić B, Stoimenov L. Big Data Analytics and Processing Platform in Czech Republic Healthcare. Applied Sciences 2020;10(5):1705
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Douglas PS, Cerqueira MD, Berman DS, Chinnaiyan K, Cohen MS, Lundbye JB, Patel RA, Sengupta PP, Soman P, Weissman NJ, Wong TC, Asch F, Bateman TM, Biesbrock G, Brinker J, Brophy D, Cerqueira M, Cohen M, Dilsizian V, Douglas PS, Dudley J, Epstein F, Gillam L, Lundbye J, McCallister B, Narula J, Reynolds D, Schoepf UJ, Shah N, Udelson JE, Valeti US, Walsh MN, Ward RP, Weigold WG, White RD, Wolinsky D, Zoghbi WA. The Future of Cardiac Imaging. JACC: Cardiovascular Imaging 2016;9(10):1211
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. Comparative Medicine in the Twenty-First Century: Where are We Now and Where Do We Go from Here?. Frontiers in Veterinary Science 2015;2
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. Open Data: Can It Prevent Research Fraud, Promote Reproducibility, and Enable Big Data Analytics In Clinical Research?. The Annals of Thoracic Surgery 2015;100(5):1539
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Ghassemi M, Naumann T, Schulam P, Beam AL, Chen IY, Ranganath R. Practical guidance on artificial intelligence for health-care data. The Lancet Digital Health 2019;1(4):e157
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Sanchez-Pinto LN, Luo Y, Churpek MM. Big Data and Data Science in Critical Care. Chest 2018;154(5):1239
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Kawazoe Y, Imai T, Ohe K. A Querying Method over RDF-ized Health Level Seven v2.5 Messages Using Life Science Knowledge Resources. JMIR Medical Informatics 2016;4(2):e12
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Pisani AR, Kanuri N, Filbin B, Gallo C, Gould M, Lehmann LS, Levine R, Marcotte JE, Pascal B, Rousseau D, Turner S, Yen S, Ranney ML. Protecting User Privacy and Rights in Academic Data-Sharing Partnerships: Principles From a Pilot Program at Crisis Text Line. Journal of Medical Internet Research 2019;21(1):e11507
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Casanovas P, Mendelson D, Poblet M. A Linked Democracy Approach for Regulating Public Health Data. Health and Technology 2017;7(4):519
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. Big data and machine learning in critical care: Opportunities for collaborative research. Medicina Intensiva (English Edition) 2019;43(1):52
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Vijayakumar S, Duggar WN, Packianathan S, Morris B, Yang CC. Chasing Zero Harm in Radiation Oncology: Using Pre-treatment Peer Review. Frontiers in Oncology 2019;9
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Celi LA, Lokhandwala S, Montgomery R, Moses C, Naumann T, Pollard T, Spitz D, Stretch R. Datathons and Software to Promote Reproducible Research. Journal of Medical Internet Research 2016;18(8):e230
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Núñez Reiz A, Martínez Sagasti F, Álvarez González M, Blesa Malpica A, Martín Benítez JC, Nieto Cabrera M, del Pino Ramírez , Gil Perdomo JM, Prada Alonso J, Celi LA, Armengol de la Hoz M, Deliberato R, Paik K, Pollard T, Raffa J, Torres F, Mayol J, Chafer J, González Ferrer A, Rey , González Luengo H, Fico G, Lombroni I, Hernandez L, López L, Merino B, Cabrera MF, Arredondo MT, Bodí M, Gómez J, Rodríguez A, Sánchez García M. Big data and machine learning in critical care: Opportunities for collaborative research. Medicina Intensiva 2019;43(1):52
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Luo EM, Newman S, Amat M, Charpignon M, Duralde ER, Jain S, Kaufman AR, Korolev I, Lai Y, Lam BD, Lipcsey M, Martinez A, Mechanic OJ, Mlabasati J, McCoy LG, Nguyen FT, Samuel M, Yang E, Celi LA. MIT COVID-19 Datathon: data without boundaries. BMJ Innovations 2021;7(1):231
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Casanovas P, Mendelson D, Poblet M. A Linked Democracy Approach for Regulating Public Health Data. SSRN Electronic Journal 2017;
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Lei H, O’Connell R, Ehwerhemuepha L, Taraman S, Feaster W, Chang A. Agile clinical research: A data science approach to scrumban in clinical medicine. Intelligence-Based Medicine 2020;3-4:100009
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Bhattarai S, Gupta A, Ali E, Ali M, Riad M, Adhikari P, Mostafa JA. Can Big Data and Machine Learning Improve Our Understanding of Acute Respiratory Distress Syndrome?. Cureus 2021;
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Viberg Johansson J, Bentzen HB, Shah N, Haraldsdóttir E, Jónsdóttir GA, Kaye J, Mascalzoni D, Veldwijk J. Preferences of the Public for Sharing Health Data: Discrete Choice Experiment. JMIR Medical Informatics 2021;9(7):e29614
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Khan Y, Zimmermann A, Jha A, Gadepally V, D'Aquin M, Sahay R. One Size Does Not Fit All: Querying Web Polystores. IEEE Access 2019;7:9598
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Almowil Z, Zhou S, Brophy S, Croxall J. Concept Libraries for Repeatable and Reusable Research: Qualitative Study Exploring the Needs of Users. JMIR Human Factors 2022;9(1):e31021
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Corti C, Nicolò E, Curigliano G. Novel immune targets for the treatment of triple-negative breast cancer. Expert Opinion on Therapeutic Targets 2021;25(10):815
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Asswad J, Marx Gómez J. Data Ownership: A Survey. Information 2021;12(11):465
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Viberg Johansson J, Bentzen HB, Mascalzoni D. What ethical approaches are used by scientists when sharing health data? An interview study. BMC Medical Ethics 2022;23(1)
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Varshini KS, Uthra RA. Extraction of Meaningful Information from Unstructured Clinical Notes Using Web Scraping. Journal of Circuits, Systems and Computers 2023;32(03)
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Safari S, Shafiekhani P. Clinical Physician Versus Data Scientist: Wearing Different Hats in Future Medicine. Precision Medicine and Clinical OMICS 2022;2(1)
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Zimolzak AJ, Davila JA, Punugoti V, Balasubramanyam A, Klotman PE, Petersen LA, Rochat RH, Liao G, Laubscher RR, Leiber L, Amos CI. Lessons learned from an enterprise-wide clinical datathon. Journal of Clinical and Translational Science 2022;6(1)
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Ishii-Rousseau JE, Seino S, Ebner DK, Vareth M, Po MJ, Celi LA, Simsekler MCE. The “Ecosystem as a Service (EaaS)” approach to advance clinical artificial intelligence (cAI). PLOS Digital Health 2022;1(2):e0000011
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Corti C, Cobanaj M, Dee EC, Criscitiello C, Tolaney SM, Celi LA, Curigliano G. Artificial intelligence in cancer research and precision medicine: Applications, limitations and priorities to drive transformation in the delivery of equitable and unbiased care. Cancer Treatment Reviews 2023;112:102498
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Findlay C, Edwards M, Hough K, Grasmeder M, Newman TA. Leveraging real-world data to improve cochlear implant outcomes: Is the data available?. Cochlear Implants International 2023;24(4):178
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. A Digital Opportunity for Patients to Manage Their Health: Turkey National Personal Health Record System (The e-Nabız). Balkan Medical Journal 2023;40(3):215
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Lokshina I, Lanting C. EVOLUTION OF REGULATORY MODELS FOR PUBLIC HEALTH DATA ECOSYSTEMS FROM A LINKED DEMOCRACY PERSPECTIVE. New Trends in Computer Sciences 2023;1(2):70
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Samad M, Angel M, Rinehart J, Kanomata Y, Baldi P, Cannesson M. Medical Informatics Operating Room Vitals and Events Repository (MOVER): a public-access operating room database. JAMIA Open 2023;6(4)
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Markopoulos D, Tsolakidis A, Triantafyllou I, Giannakopoulos GA, Skourlas C. A conceptual framework for the ICU of the future evaluated by the MIMIC-III digital archive. Global Knowledge, Memory and Communication 2024;
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Sun K, Roy A, Tobin JM. Artificial intelligence and machine learning: Definition of terms and current concepts in critical care research. Journal of Critical Care 2024;82:154792
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Li Y, Liu S, Zeng A, Wu J, Zhang J, Zhang W, Li S. Interdisciplinary Dynamics in COVID-19 Research: Examining the Role of Computer Science and Collaboration Patterns. Systems 2024;12(4):113
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According to Crossref, the following books are citing this article (DOI 10.2196/medinform.3447):
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Stone D, Rousseau J, Lai Y. Secondary Analysis of Electronic Health Records. 2016. Chapter 4:27
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Nair S, Hsu D, Celi LA. Secondary Analysis of Electronic Health Records. 2016. Chapter 3:17
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Gupta VP, Arora AK. Applications of Deep Learning and Big IoT on Personalized Healthcare Services. 2020. chapter 1:1
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Jolly S, Gupta N. International Conference on Innovative Computing and Communications. 2021. Chapter 37:477
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Ghassemi M, Celi LA, Stone DJ. Annual Update in Intensive Care and Emergency Medicine 2015. 2015. Chapter 42:573
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Chen Y, Pardo TA, Chen S. Electronic Government. 2017. Chapter 25:303
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Varshini KS, Uthra RA. Inventive Systems and Control. 2021. Chapter 44:581
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. Futuristic Trends in Networks and Computing Technologies. 2022. Chapter 68:951
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Gupta VP, Arora AK. Research Anthology on Cross-Disciplinary Designs and Applications of Automation. 2022. chapter 15:285
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Wenjuan L, Shi L, Fan Z, Zhi Y, Honggang W, Xishuang H, Wenjin Z. Innovative Computing Vol 2 - Emerging Topics in Future Internet. 2023. Chapter 3:17
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Corti C, Cobanaj M, Criscitiello C, Curigliano G. Artificial Intelligence for Medicine. 2024. :1
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