Published on in Vol 2, No 2 (2014): Jul-Dec

Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference

Journals

  1. Celi L, Ippolito A, Montgomery R, Moses C, Stone D. Crowdsourcing Knowledge Discovery and Innovations in Medicine. Journal of Medical Internet Research 2014;16(9):e216 View
  2. Sewerin P, Ostendorf B, Hueber A, Kleyer A. Big Data in der Bildgebung. Zeitschrift für Rheumatologie 2018;77(3):203 View
  3. Eytan D, Jegatheeswaran A, Mazwi M, Assadi A, Goodwin A, Greer R, Goodfellow S, Laussen P. Temporal Variability in the Sampling of Vital Sign Data Limits the Accuracy of Patient State Estimation*. Pediatric Critical Care Medicine 2019;20(7):e333 View
  4. Wellner B, Grand J, Canzone E, Coarr M, Brady P, 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 View
  5. Huddar V, Desiraju B, Rajan V, Bhattacharya S, Roy S, Reddy C. Predicting Complications in Critical Care Using Heterogeneous Clinical Data. IEEE Access 2016;4:7988 View
  6. Ding R, Arighi C, Lee J, Wu C, Vijay-Shanker K, Wilbur W. pGenN, a Gene Normalization Tool for Plant Genes and Proteins in Scientific Literature. PLOS ONE 2015;10(8):e0135305 View
  7. Jaffee E, Dang C, Agus D, Alexander B, Anderson K, Ashworth A, Barker A, Bastani R, Bhatia S, Bluestone J, Brawley O, Butte A, Coit D, Davidson N, Davis M, DePinho R, Diasio R, Draetta G, Frazier A, Futreal A, Gambhir S, Ganz P, Garraway L, Gerson S, Gupta S, Heath J, Hoffman R, Hudis C, Hughes-Halbert C, Ibrahim R, Jadvar H, Kavanagh B, Kittles R, Le Q, Lippman S, Mankoff D, Mardis E, Mayer D, McMasters K, Meropol N, Mitchell B, Naredi P, Ornish D, Pawlik T, Peppercorn J, Pomper M, Raghavan D, Ritchie C, Schwarz S, Sullivan R, Wahl R, Wolchok J, Wong S, Yung A. Future cancer research priorities in the USA: a Lancet Oncology Commission. The Lancet Oncology 2017;18(11):e653 View
  8. 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 View
  9. Nepal S, Ranjan R, Choo K. Trustworthy Processing of Healthcare Big Data in Hybrid Clouds. IEEE Cloud Computing 2015;2(2):78 View
  10. Ghassemi M, Celi L, Stone D. State of the art review: the data revolution in critical care. Critical Care 2015;19(1) View
  11. Kansagra A, Yu J, Chatterjee A, Lenchik L, Chow D, Prater A, Yeh J, Doshi A, Hawkins C, Heilbrun M, Smith S, Oselkin M, Gupta P, Ali S. Big Data and the Future of Radiology Informatics. Academic Radiology 2016;23(1):30 View
  12. Panch T, Szolovits P, Atun R. Artificial intelligence, machine learning and health systems. Journal of Global Health 2018;8(2) View
  13. Moseley E, Hsu D, Stone D, Celi L. Beyond Open Big Data: Addressing Unreliable Research. Journal of Medical Internet Research 2014;16(11):e259 View
  14. Johnson A, Ghassemi M, Nemati S, Niehaus K, Clifton D, Clifford G. Machine Learning and Decision Support in Critical Care. Proceedings of the IEEE 2016;104(2):444 View
  15. Eytan D, Goodwin A, Greer R, Guerguerian A, Mazwi M, Laussen P. Distributions and Behavior of Vital Signs in Critically Ill Children by Admission Diagnosis*. Pediatric Critical Care Medicine 2018;19(2):115 View
  16. Štufi M, Bačić B, Stoimenov L. Big Data Analytics and Processing Platform in Czech Republic Healthcare. Applied Sciences 2020;10(5):1705 View
  17. Douglas P, Cerqueira M, Berman D, Chinnaiyan K, Cohen M, Lundbye J, Patel R, Sengupta P, Soman P, Weissman N, Wong T, Asch F, Bateman T, Biesbrock G, Brinker J, Brophy D, Cerqueira M, Cohen M, Dilsizian V, Douglas P, Dudley J, Epstein F, Gillam L, Lundbye J, McCallister B, Narula J, Reynolds D, Schoepf U, Shah N, Udelson J, Valeti U, Walsh M, Ward R, Weigold W, White R, Wolinsky D, Zoghbi W. The Future of Cardiac Imaging. JACC: Cardiovascular Imaging 2016;9(10):1211 View
  18. Mobasheri A. Comparative Medicine in the Twenty-First Century: Where are We Now and Where Do We Go from Here?. Frontiers in Veterinary Science 2015;2 View
  19. Myers P. 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 View
  20. Ghassemi M, Naumann T, Schulam P, Beam A, Chen I, Ranganath R. Practical guidance on artificial intelligence for health-care data. The Lancet Digital Health 2019;1(4):e157 View
  21. Sanchez-Pinto L, Luo Y, Churpek M. Big Data and Data Science in Critical Care. Chest 2018;154(5):1239 View
  22. 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 View
  23. Pisani A, Kanuri N, Filbin B, Gallo C, Gould M, Lehmann L, Levine R, Marcotte J, Pascal B, Rousseau D, Turner S, Yen S, Ranney M. 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 View
  24. Casanovas P, Mendelson D, Poblet M. A Linked Democracy Approach for Regulating Public Health Data. Health and Technology 2017;7(4):519 View
  25. Núñez Reiz A. Big data and machine learning in critical care: Opportunities for collaborative research. Medicina Intensiva (English Edition) 2019;43(1):52 View
  26. Vijayakumar S, Duggar W, Packianathan S, Morris B, Yang C. Chasing Zero Harm in Radiation Oncology: Using Pre-treatment Peer Review. Frontiers in Oncology 2019;9 View
  27. Celi L, 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 View
  28. Núñez Reiz A, Martínez Sagasti F, Álvarez González M, Blesa Malpica A, Martín Benítez J, Nieto Cabrera M, del Pino Ramírez Á, Gil Perdomo J, Prada Alonso J, Celi L, Armengol de la Hoz M, Deliberato R, Paik K, Pollard T, Raffa J, Torres F, Mayol J, Chafer J, González Ferrer A, Rey Á, González Luengo H, Fico G, Lombroni I, Hernandez L, López L, Merino B, Cabrera M, Arredondo M, 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 View
  29. Luo E, Newman S, Amat M, Charpignon M, Duralde E, Jain S, Kaufman A, Korolev I, Lai Y, Lam B, Lipcsey M, Martinez A, Mechanic O, Mlabasati J, McCoy L, Nguyen F, Samuel M, Yang E, Celi L. MIT COVID-19 Datathon: data without boundaries. BMJ Innovations 2021;7(1):231 View
  30. Casanovas P, Mendelson D, Poblet M. A Linked Democracy Approach for Regulating Public Health Data. SSRN Electronic Journal 2017 View
  31. 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 View
  32. Bhattarai S, Gupta A, Ali E, Ali M, Riad M, Adhikari P, Mostafa J. Can Big Data and Machine Learning Improve Our Understanding of Acute Respiratory Distress Syndrome?. Cureus 2021 View
  33. Viberg Johansson J, Bentzen H, Shah N, Haraldsdóttir E, Jónsdóttir G, Kaye J, Mascalzoni D, Veldwijk J. Preferences of the Public for Sharing Health Data: Discrete Choice Experiment. JMIR Medical Informatics 2021;9(7):e29614 View
  34. 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 View
  35. 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 View
  36. 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 View
  37. Asswad J, Marx Gómez J. Data Ownership: A Survey. Information 2021;12(11):465 View
  38. Viberg Johansson J, Bentzen H, Mascalzoni D. What ethical approaches are used by scientists when sharing health data? An interview study. BMC Medical Ethics 2022;23(1) View
  39. Varshini K, Uthra R. Extraction of Meaningful Information from Unstructured Clinical Notes Using Web Scraping. Journal of Circuits, Systems and Computers 2023;32(03) View
  40. Safari S, Shafiekhani P. Clinical Physician Versus Data Scientist: Wearing Different Hats in Future Medicine. Precision Medicine and Clinical OMICS 2022;2(1) View
  41. Zimolzak A, Davila J, Punugoti V, Balasubramanyam A, Klotman P, Petersen L, Rochat R, Liao G, Laubscher R, Leiber L, Amos C. Lessons learned from an enterprise-wide clinical datathon. Journal of Clinical and Translational Science 2022;6(1) View
  42. Ishii-Rousseau J, Seino S, Ebner D, Vareth M, Po M, Celi L, Simsekler M. The “Ecosystem as a Service (EaaS)” approach to advance clinical artificial intelligence (cAI). PLOS Digital Health 2022;1(2):e0000011 View
  43. Corti C, Cobanaj M, Dee E, Criscitiello C, Tolaney S, Celi L, 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 View
  44. Findlay C, Edwards M, Hough K, Grasmeder M, Newman T. Leveraging real-world data to improve cochlear implant outcomes: Is the data available?. Cochlear Implants International 2023;24(4):178 View
  45. Birinci Ş. 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 View
  46. 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 View
  47. 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) View
  48. Markopoulos D, Tsolakidis A, Triantafyllou I, Giannakopoulos G, Skourlas C. A conceptual framework for the ICU of the future evaluated by the MIMIC-III digital archive. Global Knowledge, Memory and Communication 2024 View
  49. Sun K, Roy A, Tobin J. Artificial intelligence and machine learning: Definition of terms and current concepts in critical care research. Journal of Critical Care 2024;82:154792 View
  50. 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 View

Books/Policy Documents

  1. Stone D, Rousseau J, Lai Y. Secondary Analysis of Electronic Health Records. View
  2. Nair S, Hsu D, Celi L. Secondary Analysis of Electronic Health Records. View
  3. Gupta V, Arora A. Applications of Deep Learning and Big IoT on Personalized Healthcare Services. View
  4. Jolly S, Gupta N. International Conference on Innovative Computing and Communications. View
  5. Ghassemi M, Celi L, Stone D. Annual Update in Intensive Care and Emergency Medicine 2015. View
  6. Chen Y, Pardo T, Chen S. Electronic Government. View
  7. Varshini K, Uthra R. Inventive Systems and Control. View
  8. Choudhary R. Futuristic Trends in Networks and Computing Technologies. View
  9. Gupta V, Arora A. Research Anthology on Cross-Disciplinary Designs and Applications of Automation. View
  10. Wenjuan L, Shi L, Fan Z, Zhi Y, Honggang W, Xishuang H, Wenjin Z. Innovative Computing Vol 2 - Emerging Topics in Future Internet. View
  11. Corti C, Cobanaj M, Criscitiello C, Curigliano G. Artificial Intelligence for Medicine. View
  12. Vetrivel S, Arun V, Maheswari R, Saravanan T. Machine Learning and Generative AI in Smart Healthcare. View