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Connection

Michael Rosenberg to Electronic Health Records

This is a "connection" page, showing publications Michael Rosenberg has written about Electronic Health Records.

 
Connection Strength
 
 
 
1.667
 
  1. Simon ST, Trinkley KE, Malone DC, Rosenberg MA. Interpretable Machine Learning Prediction of Drug-Induced QT Prolongation: Electronic Health Record Analysis. J Med Internet Res. 2022 12 01; 24(12):e42163.
    View in: PubMed
    Score: 0.534
  2. Mandair D, Tiwari P, Simon S, Colborn KL, Rosenberg MA. Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data. BMC Med Inform Decis Mak. 2020 10 02; 20(1):252.
    View in: PubMed
    Score: 0.460
  3. Tiwari P, Colborn KL, Smith DE, Xing F, Ghosh D, Rosenberg MA. Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation. JAMA Netw Open. 2020 01 03; 3(1):e1919396.
    View in: PubMed
    Score: 0.436
  4. Trinkley KE, Pell JM, Martinez DD, Maude NR, Hale G, Rosenberg MA. Assessing Prescriber Behavior with a Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome. Appl Clin Inform. 2021 01; 12(1):190-197.
    View in: PubMed
    Score: 0.118
  5. Simon ST, Mandair D, Tiwari P, Rosenberg MA. Prediction of Drug-Induced Long QT Syndrome Using Machine Learning Applied to Harmonized Electronic Health Record Data. J Cardiovasc Pharmacol Ther. 2021 07; 26(4):335-340.
    View in: PubMed
    Score: 0.118
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.

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