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- W2570898045 abstract "We describe a three-step procedure to separate patients with myocardial infarction from a control group based on SELDI-TOF mass spectra. The procedure returns features (“biomarkers”) that are strongly present in one of the two groups. These features should allow future subjects to be classified as at-risk of myocardial infarction. The algorithm uses morphological operations to reduce noise in the input data as well as for performing baseline correction. In contrast to previous approaches on SELDI-TOF spectra, we avoid black-box machine learning procedures and use only features (protein masses) that are easy to interpret." @default.
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- W2570898045 date "2006-01-01" @default.
- W2570898045 modified "2023-09-23" @default.
- W2570898045 title "Discovering Biomarkers for Myocardial Infarction from SELDI-TOF Spectra." @default.
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