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This work proposes a pattern mining approach to learn event detection models from complex multivariate temporal data, such as electronic health records. We present Recent Temporal Pattern mining, a novel approach for efficiently finding predictive patterns for event detection problems. This approach first converts the time series data into time-interval sequences of temporal abstractions. It then constructs more complex time-interval patterns backward in time using temporal operators. We alsodoi:10.1007/s10115-015-0819-6 pmid:26752800 pmcid:PMC4704806 fatcat:7pelhltbpzbeziaptxekgzol5q