This paper proposes a parameterized Support Vector Machine (ParaSVM) approach for modeling the Drug Concentration to Time (DCT) curves. It combines the merits of Support Vector Machine (SVM) algorithm that considers various patient features and an analytical model that approxi- mates the predicted DCT points and enables curve calibrations using occasional real Therapeutic Drug Monitoring (TDM) measurements. The RANSAC algorithm is applied to construct the parameter library for the relevant basis functions. We show an example of using ParaSVM to build DCT curves and then calibrate them by TDM measurements on imatinib case study.
Pascal Frossard, Thomas Maugey, Yu Gao
Volkan Cevher, Catherine Dehollain, Mahsa Shoaran, Cosimo Aprile, Yusuf Leblebici, Luca Baldassarre, Kerim Türe, Gürkan Yilmaz, Franco Maloberti
Pascal Frossard, Francesca De Simone