A text-mining approach to obtain detailed treatment information from free-text fields in population-based cancer registries: A study of non-small cell lung cancer in California.
Frances B MaguireCyllene R MorrisArti Parikh-PatelRosemary D CressTheresa H M KeeganChin-Shang LiPatrick S LinKenneth W KizerPublished in: PloS one (2019)
SAS-based text mining of free-text data can accurately detect systemic treatments administered to patients and save considerable time compared to manual review, maximizing the utility of the extant information in population-based cancer registries for comparative effectiveness research.
Keyphrases
- smoking cessation
- papillary thyroid
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- peritoneal dialysis
- prognostic factors
- health information
- healthcare
- lymph node metastasis
- electronic health record
- squamous cell carcinoma
- replacement therapy
- machine learning
- patient reported outcomes
- social media