DEVELOPMENT AND VALIDATION OF AN INTERPRETABLE MACHINE LEARNING MODEL FOR PREDICTING LEFT ATRIAL THROMBUS OR SPONTANEOUS ECHO CONTRAST IN NON-VALVULAR ATRIAL FIBRILLATION PATIENTS.

PurposeLeft atrial thrombus or spontaneous echo contrast (LAT/SEC) are widely recognized as significant contributors to cardiogenic embolism in non-valvular atrial fibrillation (NVAF).This study aimed to construct and validate an interpretable predictive model of LAT/SEC risk in NVAF patients using machine learning (ML) methods.MethodsElectronic me

In this note, the application of a plant model-based fault here detection method for nonlinear control systems on aircraft takeoff is introduced.This method utilizes non-deterministic finite-state automata, which approximate the fault-free dynamics of the plant.The aforementioned automaton is computed in a preliminary step while during evolution of

We study a class of games which glitter foam vellen action models the competition among agents to access some service provided by distributed service units and which exhibits congestion and frustration phenomena when service units have limited capacity.We propose a technique, based on the cavity method of statistical physics, to characterize the fu