Exploring the Association of Cancer and Depression in Electronic Health Records: Combining Encoded Diagnosis and Mining Free-Text Clinical Notes.
Angela LeisDavid CasadevallJoan AlbanellMargarita PossoFrancesc MaciàXavier CastellsJuan Manuel Ramírez-AnguitaJordi Martinez RoldanLaura I FurlongFerran SanzFrancesco RonzanoMiguel Angel MayerPublished in: JMIR cancer (2022)
This study provides new clinical evidence of the depression-cancer comorbidity and supports the use of natural language processing for extracting and analyzing free-text clinical notes from electronic health records, contributing to the identification of additional clinical data that complements those provided by coded data to improve the management of these patients.
Keyphrases
- electronic health record
- clinical decision support
- end stage renal disease
- depressive symptoms
- papillary thyroid
- chronic kidney disease
- adverse drug
- newly diagnosed
- squamous cell carcinoma
- peritoneal dialysis
- sleep quality
- machine learning
- data analysis
- artificial intelligence
- childhood cancer
- patient reported outcomes