Ascertainment of Veterans With Metastatic Prostate Cancer in Electronic Health Records: Demonstrating the Case for Natural Language Processing.
Patrick R AlbaAnthony GaoKyung Min LeeTori Anglin-FooteBrian RobisonEvangelia KatsoulakisBrent S RoseOlga EfimovaJeffrey P FerraroOlga V PattersonJeremy B SheltonScott L DuvallJulie A LynchPublished in: JCO clinical cancer informatics (2021)
Clinical documentation of mPCa is highly reliable. NLP can be leveraged to improve PCa data. When compared to other methods, NLP identified a significantly greater number of patients. NLP can be used to augment cancer registry data, facilitate research inquiries, and identify patients who may benefit from innovations in mPCa treatment.
Keyphrases
- electronic health record
- prostate cancer
- clinical decision support
- end stage renal disease
- adverse drug
- chronic kidney disease
- newly diagnosed
- ejection fraction
- squamous cell carcinoma
- small cell lung cancer
- prognostic factors
- peritoneal dialysis
- papillary thyroid
- big data
- autism spectrum disorder
- squamous cell
- lymph node metastasis
- artificial intelligence
- patient reported
- replacement therapy
- childhood cancer
- smoking cessation