Prediction of Cancer Symptom Trajectory Using Longitudinal Electronic Health Record Data and Long Short-Term Memory Neural Network.
Sena ChaeW Nick StreetNaveenkumar RamarajuStéphanie Gilbertson WhitePublished in: JCO clinical cancer informatics (2024)
We can successfully predict patients' symptom trajectories with a prediction model, built with sparse assessment data, using routinely collected nursing documentation. The results of this project can be applied to better individualize symptom management to support cancer patients' quality of life.
Keyphrases
- electronic health record
- neural network
- clinical decision support
- end stage renal disease
- patient reported
- adverse drug
- ejection fraction
- newly diagnosed
- quality improvement
- healthcare
- chronic kidney disease
- peritoneal dialysis
- papillary thyroid
- prognostic factors
- mental health
- depressive symptoms
- big data
- squamous cell
- patient reported outcomes
- young adults