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Objective: This paper presents the development of a fast and robust method which can be applied to multichannel physiologic signals for the purpose of either removing a selected interfering signal or separating signals that arise from temporally correlated and spatially distributed signals such as maternal or fetal cardiac waveform recordings. Methods: Projection operators based upon both the weighted...
Medical data accuracy is crucial for providing reliable remote healthcare services for patients. To this end, data accuracy assessment mechanisms must be developed. Prediction algorithms may be used in order to address this issue. This paper extends previous studies by investigating the relevance of different statistical concepts in modeling and predicting the variance instability of medical data...
Leaf area index (LAI) is an important biophysical variable indicating forest growth. A major challenge is to improve the LAI estimates for large forest-covered areas. One way to obtain LAI value is using current LAI products. Current LAI products contain many uncertainties and need improvement. This paper aims to improve forest LAI estimates by combining satellite reflectance derived LAI with forest...
We compare the dynamic Bayesian network and k-nearest neighbor-based predictors for the occurrence of acute hypotensive episodes (AHE) with respect to various data conditions (size, class balance ratio) and problem definition settings (lag, lead time). From our dataset extracted from the large ICU physiological waveform repository of MIMIC2 database, we find that both models are effective for predicting...
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