Representation of clinical information in outpatient oncology for prognosis using regression
Department of Electrical and Computer Engineering, Department of Computer Science, Center for Data Sciences
The determination of length of survival, or prognosis, is often viewed through statistical hazard models or with respect to a future reference time point in a classification approach (e.g., survival after 2 or 5 years). In this research, regression was used to determine a patient’s prognosis. Also, multiple behavioral representations of clinical data, including difference trends and splines, are considered for predictor variables, which is different from demographic and tumor characteristics often used. With this approach the amount of clinical samples considered from the available patient data in the model in conjunction with the behavioral representation was explored. The models with the best prognostic performance had data representations that included limited clinical samples and some behavioral interpretations.
Advances in Science, Technology and Engineering SystemsJournal
Representation of clinical information in outpatient oncology for prognosis using regression.
Advances in Science, Technology and Engineering SystemsJournal,
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