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SM ISO690:2012 IAPĂSCURTĂ, Victor. A Less Traditional Approach to Biomedical Signal Processing for Sepsis Prediction. In: Nanotechnologies and Biomedical Engineering, Ed. 5, 3-5 noiembrie 2021, Chişinău. Chişinău: Pontos, 2021, Ediția 5, p. 78. ISBN 978-9975-72-592-7. |
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Nanotechnologies and Biomedical Engineering Ediția 5, 2021 |
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Conferința "Nanotechnologies and Biomedical Engineering" 5, Chişinău, Moldova, 3-5 noiembrie 2021 | ||||||
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Pag. 78-78 | ||||||
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Most of the data generated by monitors in a clinical setting represent time series data which can be visualized and subsequently used for decision making. This usually is the simplest part. A more challenging aspect is using this data for more complex task like machine learning with the same goal – computer assisted decisions. Within this challenge raw biomedical signal data need to be preprocessed before being passed to the machine learning algorithm. This can be done by a multitude of methods. A number of such methods comes from the field of Algorithmic Complexity and although of a promising nature, these particular methods are poorly explored yet. The current research presents an example of applying the Block Decomposition Method to data routinely generated by patients in a modern Intensive Care Unit. The final goal of a larger research, the actual research being part of, is building a system for early sepsis prediction. |
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