Ascertaining provider-level implicit bias in electronic health records with rules-based natural language processing: A pilot study in the case of prostate cancer.

Ascertaining provider-level implicit bias in electronic health records with rules-based natural language processing: A pilot study in the case of prostate cancer.

Show other versions (1)

<h4>Purpose</h4>Implicit, unconscious biases in medicine are personal attitudes about race, ethnicity, gender, and other characteristics that may lead to discriminatory patterns of care. However, there is no consensus on whether implicit bias represents a true predictor of differential c...

Full description

Saved in:
Bibliographic Details
Main Authors: Ashwin Ramaswamy, Michael Hung, Joe Pelt, Parsa Iranmahboub, Lina P Calderon, Ian S Scherr, Gerald Wang, David Green, Neal Patel, Timothy D McClure, Christopher Barbieri, Jim C Hu, Charlotta Lindvall, Douglas S Scherr
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2024-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0314989
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items