Guilherme O. Campos

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The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a(More)
OBJECTIVES Correlate arterial lactate levels during the intraoperative period of children undergoing cardiac surgery and the occurrence of complications in the postoperative period. AIM Arterial lactate levels can indicate hypoperfusion states, serving as prognostic markers of morbidity and mortality in this population. BACKGROUND Anesthesia for cardiac(More)
BACKGROUND Anesthesia for pediatric cardiac surgery is systematically performed in severely ill patients under abnormal physiological conditions. In the intraoperative period, there are significant variations in blood volume, body temperature, plasma composition, and tissue blood flow, in addition to activation of inflammation, with important consequences.(More)
The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of dierent standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a signicant(More)
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