Published on in Vol 5, No 4 (2017): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/7380, first published .
Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon

Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon

Promoting Secondary Analysis of Electronic Medical Records in China: Summary of the PLAGH-MIT Critical Data Conference and Health Datathon

Journals

  1. Cai M, Liu E, Zhang R, Lin X, Rigdon S, Qian Z, Belue R, Chang J. <p>Comparing the Performance of Charlson and Elixhauser Comorbidity Indices to Predict In-Hospital Mortality Among a Chinese Population</p>. Clinical Epidemiology 2020;Volume 12:307 View
  2. Wang J, Huang J, Cheung C, Wong W, Cheung N, Wong M. Adoption of an Electronic Patient Record Sharing Pilot Project: Cross-Sectional Survey. Journal of Medical Internet Research 2020;22(4):e13761 View
  3. Verheij R, Curcin V, Delaney B, McGilchrist M. Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse. Journal of Medical Internet Research 2018;20(5):e185 View
  4. Cosgriff C, Celi L, Stone D. Critical Care, Critical Data. Biomedical Engineering and Computational Biology 2019;10:117959721985656 View
  5. Ni K, Chu H, Zeng L, Li N, Zhao Y. Barriers and facilitators to data quality of electronic health records used for clinical research in China: a qualitative study. BMJ Open 2019;9(7):e029314 View
  6. 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
  7. Paris N, Lamer A, Parrot A. Transformation and Evaluation of the MIMIC Database in the OMOP Common Data Model: Development and Usability Study. JMIR Medical Informatics 2021;9(12):e30970 View
  8. Wang M, Li S, Zheng T, Li N, Shi Q, Zhuo X, Ding R, Huang Y. Big Data Health Care Platform With Multisource Heterogeneous Data Integration and Massive High-Dimensional Data Governance for Large Hospitals: Design, Development, and Application. JMIR Medical Informatics 2022;10(4):e36481 View
  9. Wang C, Yao C, Chen P, Shi J, Gu Z, Zhou Z, Abdulhay E. Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management. Journal of Healthcare Engineering 2021;2021:1 View
  10. Wang C, Yao C, Chen P, Shi J, Gu Z, Zhou Z. Artificial Intelligence Algorithm with ICD Coding Technology Guided by Embedded Electronic Medical Record System in Medical Record Information Management. Microprocessors and Microsystems 2023:104962 View
  11. Sobel J, Almog R, Celi L, Yablowitz M, Eytan D, Behar J. How to organise a datathon for bridging between data science and healthcare? Insights from the Technion-Rambam machine learning in healthcare datathon event. BMJ Health & Care Informatics 2023;30(1):e100736 View
  12. Wang D, Niu Y, Chen D, Li C, Liu F, Feng Z, Cao X, Zhang L, Cai G, Chen X, Li P. Acute kidney injury in hospitalized patients with nonmalignant pleural effusions: a retrospective cohort study. BMC Nephrology 2024;25(1) View
  13. Wang D, Niu Y, Ma Y, Tang L, Zhang Q, Zhang L, Sun X, Mei Y, Cai G, Chen X, Li P. Clinical characteristics and prognostic factors of non-malignant pleural effusions in hospitalised patients: a retrospective cohort study. BMJ Open 2024;14(7):e077980 View

Books/Policy Documents

  1. Zarbiv S, Fagleman E, Dangayach N. Modern Monitoring in Anesthesiology and Perioperative Care. View
  2. Gao X, Xu J. Smart Health. View
  3. Chang A. Intelligence-Based Medicine. View