CONTRASTIVE LEARNING WITH TRANSFORMER FOR ADVERSE ENDPOINT PREDICTION IN PATIENTS ON DAPT POST-CORONARY STENT IMPLANTATION

Contrastive learning with transformer for adverse endpoint prediction in patients on DAPT post-coronary stent implantation

BackgroundEffective management of dual antiplatelet therapy (DAPT) following drug-eluting stent (DES) implantation is crucial for preventing adverse events.Traditional prognostic tools, such as rule-based methods or Cox regression, despite their widespread use and ease, tend to yield moderate predictive accuracy within predetermined timeframes.This

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Design of a Robust sliding mode controller for bioreactor cultures in overflow metabolism via an interdisciplinary approach

Microorganism culture is highly complex due to the different metabolic pathways, which are very complex.A metabolic phenomenon Footwear called overflow is a challenge to overcome in automatic control tasks of microorganism cultures.In this study, a nonlinear algorithm by sliding modes (sliding mode nonlinear control, SMNC) is proposed for the robus

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