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Congestive heart failure is among leading genesis of concern that requires an immediate medical attention. Among various cardiac disorders, left ventricular systolic dysfunction is one of the well known cardiovascular disease which causes sudden congestive heart failure. The irregular functioning of a heart can be diagnosed through some of the clinical attributes, such as ejection fraction, serum creatinine etcetera. However, due to availability of a limited data related to the death events of patients suffering from left ventricular systolic dysfunction, a critical level of thresholds of clinical attributes cannot be estimated with higher precision. Hence, this paper proposes a novel pseudo reinforcement learning algorithm which overcomes a problem of majority class skewness in a limited dataset by appending a synthetic dataset across minority data space. The proposed pseudo agent in the algorithm continuously senses …