KOAD implemented automatic ICU signalling and error minimization
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In this paper, a previously developed algorithm based on self implementation and kernel mapping is executed in medical field to develop an automated, ICU signalling. The method is taken into consideration because it is adaptive, portable and has lower complexity in comparison to contemporary approaches. The proposed algorithm takes in set of different medical parameters to monitor the conditions of individual patients in an ICU. Application of real data and the learning mechanism of underlying patterns of the algorithm results in instantaneous detection and alarming in response to critical circumstances. In addition, the system yields recognition's with minimum false alarms.