TEXTOMICS

TEXTOMICS is a python-based generalizable NLP tool for extracting physician-reported pain scores from patients’ consultation notes.

TEXTOMICS is using UMLS and METAMAP libraries for medical semantic extraction. Sets of rules have been developed for negation detection and excluding hypothetical, conditional and historical mentions of the pain.

Publications describing this code include:

• Hossein Naseri, Kamran Kafi, Sonia Skamene, Marwan Tolba, Mame Daro Faye, Paul Ramia, Julia Khriguian, John Kildea (2021). Development of a generalizable natural language processing pipeline to extract physician-reported pain from clinical reports - Generated using publicly-available datasets and tested on institutional clinical reports for cancer patients with bone metastases. In Journal of Biomedical Informatics.
• Hossein Naseri, Kam Kafi, Sonia Skamene, Marwan Tolba, Mame Daro Faye, Paul Ramia, Julia Khriguian, John Kildea (2021). Development of a generalizable natural language processing pipeline to extract physician-reported pain scores from clinical reports in radiation oncology. COMP ASM 2021.