Identify radiology reports with post-traumatic hemorrhage
Project description
traumascanner
Identify radiology text-reports of patients with post-traumatic hemorrhage
Installation
$ pip install traumascanner
Usage
Use traumaScanner()
to identify patients with post-traumatic hemorrhage from radiology text reports.
traumaScanner()
is a key-word matching/regular expression (regex) and rules-based algorithm for identifying patients with post-traumatic hemorrhage after a traumatic brain injury (TBI).
In brief, the algorithm functions as follows:
- Identifies radiology reports with at least one of the provided set of trauma-related keywords
- Considers negation to remove false positive trauma related reports
- Identifies and removes reports without hemorrhage
The function will output the following csv files:
- 01_potential_trauma_reports.csv - all radiology reports which matched at least one keyword
- 02_false_postive_trauma_reports.csv - the subset of potential_trauma_reports identified as being likely false positive for trauma
- 03_trauma_no_hemorrhage_reports.csv - the subset of potential_trauma_reports which had no hemorrhage
- 04_resucued_reports.csv - the subset of trauma_no_hemorrhage_reports which were likely false negatives
- 05_post_traumatic_hemorrhage_reports - the complete set of post-traumatic hemorrhage reports identified via the
traumaScanner()
algorithm.
License
traumascanner
was created by Meghan Hutch. It is licensed under the terms of the MIT license.
Credits
traumascanner
was created with cookiecutter
and the py-pkgs-cookiecutter
template.
Project details
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