Harvard Catalyst Profiles

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David Westfall Bates, M.D.

Co-Author

This page shows the publications co-authored by David Bates and Wenyu Song.
Connection Strength

1.239
  1. Key use cases for artificial intelligence to reduce the frequency of adverse drug events: a scoping review. Lancet Digit Health. 2022 02; 4(2):e137-e148.
    View in: PubMed
    Score: 0.243
  2. Predicting pressure injury using nursing assessment phenotypes and machine learning methods. J Am Med Inform Assoc. 2021 03 18; 28(4):759-765.
    View in: PubMed
    Score: 0.232
  3. Assessing the International Transferability of a Machine Learning Model for Detecting Medication Error in the General Internal Medicine Clinic: Multicenter Preliminary Validation Study. JMIR Med Inform. 2021 Jan 27; 9(1):e23454.
    View in: PubMed
    Score: 0.229
  4. Genome-wide association analysis of opioid use disorder: A novel approach using clinical data. Drug Alcohol Depend. 2020 12 01; 217:108276.
    View in: PubMed
    Score: 0.224
  5. Using whole genome scores to compare three clinical phenotyping methods in complex diseases. Sci Rep. 2018 07 27; 8(1):11360.
    View in: PubMed
    Score: 0.193
  6. Sequential coupling of dry and wet COVID-19 screening to reduce the number of quarantined individuals. Comput Methods Programs Biomed. 2022 May; 218:106715.
    View in: PubMed
    Score: 0.062
  7. Re-tooling an Existing Clinical Quality Measure for Chronic Opioid Use to an Electronic Clinical Quality Measure (eCQM) for Post-Operative Opioid Prescribing: Development and Testing of Draft Specifications. AMIA Annu Symp Proc. 2020; 2020:1200-1209.
    View in: PubMed
    Score: 0.057
Connection Strength
The connection strength for co-authors is the sum of the scores for each of their shared publications.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.