Description of a weakly supervised machine learning approach for extracting treatment-related side effects (Urinary Incontinence) following prostate cancer therapy from multiple types of free-text clinical narratives, including progress notes, discharge summaries, history and physical notes. Prostatectomy surgery and radiation therapy are our treatments of interest for prostate cancer.

Information
Phenotype ID: 
1404
Date Created: 
Wednesday, January 15, 2020
Status: 
Final
List on the Collaboration Phenotypes List
Contact information
Authors: 
Imon Banerjee, Kevin Li, Martin Seneviratne, Michelle Ferrari, Tina Seto, James D Brooks, Daniel L Rubin, Tina Hernandez-Boussard
Institution: 
Stanford University
Unstructured Data: 
NLP
Structured data: 
CPT
ICD10
ICD9
Demographics
Gender: 
Male
Age: 
Adult
Race: 
Arctic (Siberian, Eskimo, etc.)
Black (African American, West African, Ethiopian, etc.)
Caucasian (European)
Caucasian (North African, Middle East, Other)
East Asian (Mongol, Tibetan, Korean, Japanese, Thai, etc.)
Indigenous Australian
Mixed Race
Native American
Other Race
Pacific Islander (Polynesian, Micronesian, Hawaiian, etc.)
Files: 
File PheKB_UI.docx

Suggested Citation

Imon Banerjee, Kevin Li, Martin Seneviratne, Michelle Ferrari, Tina Seto, James D Brooks, Daniel L Rubin, Tina Hernandez-Boussard . Stanford University. Urinary Incontinence. PheKB; 2020 Available from: https://www.phenotyping.org/phenotype/1404

PubMed References

31032481