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Changes in the ECG ST segment are often observed in patients with myocardial ischaemia. However, non-ischaemic changes in ST level are also common thereby limiting ischaemia detection accuracy. The aim of this study was to devise an algorithm and determine its accuracy in distinguishing between ischaemic and non-ischaemic changes in the ECG ST-segment, using expertly annotated ECG data sets as a gold standard reference. The algorithm considered only the change in ST relative to a baseline ST level (ΔST) provided by the PhysioNet database, and based on simple level thresholding within specified time windows. An initial score of 82.3% (accuracy 91.1%, with sensitivity 99.0% and specificity 88.8%) was achieved for the learning set. By making slight modifications to the algorithm and introducing principal components of ST it was not possible to improve the original algorithm. The original algorithm was therefore left as our challenge entry achieving an accuracy of 90.7% for the test data set (score of 81.4%, entry 1, 1 May 2003).