clinsent: sentiment measurement in clinical notes

Key functionality

• Keyword-based sentiment measurement
• Sentence segmentation
• To Add: Deep learning-based sentiment measurement

This package is a work in progress.

Citation: Kennedy et al. (2023).

Install

Python

Install the most recent code on GitHub via pip:

pip install git+https://github.com/ck37/clinsent/

Dependencies

Python

This package is tested with python version 3.8, but 3.9 should also work.

Examples

Python

Keyword analysis

from clinsent import KeywordFinder

kwf = KeywordFinder()
text = 'bp is improving, but o2 worsening'
hits, score = kwf.run(text)
print('Score:', score)
print('Hits:', hits)

Score: 0.5
Hits: {'improving': 1, 'worsening': 1}

Sentence segmentation

from clinsent import sentence_segment

sentence_df = sentence_segment("Patient has low bp. Hx of poor a1c control.")
print(sentence_df)

   sent_num                     text  chars  words
0         0      Patient has low bp.     19      5
1         1  Hx of poor a1c control.     23      6

Deep learning analysis

# Add example here.

R

Examples to be added.

References

Kennedy, Chris J, Catherine Chiu, Allyson Cook Chapman, Oksana Gologorskaya, Hassan Farhan, Mary Han, Macgregor Hodgson, Daniel Lazzareschi, Deepshikha Ashana, Sei Lee, Alexander K Smith, Edie Espejo, John Boscardin, Romain Pirracchio, and Julien Cobert. 2023. “Negativity and Positivity in the ICU: Exploratory Development of Automated Sentiment Capture in the Electronic Health Record.” Crit Care Explor 5 (10): e0960. https://doi.org/10.1097/CCE.0000000000000960.