In this paper, we present a new approach (Kalman Filter Smoothing) to estimate and forecast survival\nof Diabetic and Non Diabetic Coronary Artery Bypass Graft Surgery (CABG) patients. Survival proportions\nof the patients are obtained from a lifetime representing parametric model (Weibull distribution\nwith Kalman Filter approach). Moreover, an approach of complete population (CP) from its\nincomplete population (IP) of the patients with 12 years observations/follow-up is used for their\nsurvival analysis [1]. The survival proportions of the CP obtained from Kaplan Meier method are\nused as observed values t y at time t (input) for Kalman Filter Smoothing process to update time\nvarying parameters. In case of CP, the term representing censored observations may be dropped\nfrom likelihood function of the distribution. Maximum likelihood method, in-conjunction with Davidon-\nFletcher-Powell (DFP) optimization method [2] and Cubic Interpolation method is used in estimation\nof the survivor�s proportions. The estimated and forecasted survival proportions of CP of the\nDiabetic and Non Diabetic CABG patients from the Kalman Filter Smoothing approach are presented\nin terms of statistics, survival curves, discussion and conclusion.
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