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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Endoscopic Ultrasound Features Of Multiple Endocrine Neoplasia Type 1-Related Versus Sporadic Pancreatic Neuroendocrine Tumors: A Single-Center Retrospective Study, Gianluca Tamagno, Vanessa Scherer, Alberto Caimo, Simona Bergmann, Peter Kann
Endoscopic Ultrasound Features Of Multiple Endocrine Neoplasia Type 1-Related Versus Sporadic Pancreatic Neuroendocrine Tumors: A Single-Center Retrospective Study, Gianluca Tamagno, Vanessa Scherer, Alberto Caimo, Simona Bergmann, Peter Kann
Articles
Pancreatic neuroendocrine tumors (pNETs) can occur in patients with a familial syndrome either as multiple endocrine neoplasia type 1 (MEN-1) or as sporadic tumors. Endoscopic ultrasound (EUS) has become one of the first-line investigations for pNET characterization. The ultrasonographic features of pNETs may differ depending on the familial versus sporadic pathogenesis of the tumor. Therefore, the EUS findings could help and direct the definition of a pNET with an impact on the most appropriate diagnostic and ther- apeutic patient management. Methods: In this single-center retrospective study, we reviewed the EUS features of 94 pNETs from 37 MEN-1 patients and 15 …
Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez
Non-Linear Machine Learning With Active Sampling For Mox Drift Compensation, Tamara Matthews, Muhammad Iqbal, Horacio Gonzalez-Velez
Conference papers
Abstract—Metal oxide (MOX) gas detectors based on SnO2 provide low-cost solutions for real-time sensing of complex gas mixtures for indoor ambient monitoring. With high sensitivity under ideal conditions, MOX detectors may have poor longterm response accuracy due to environmental factors (humidity and temperature) along with sensor aging, leading to calibration drifts. Finding a simple and efficient solution to correct such calibration drifts has been the subject of numerous studies but remains an open problem. In this work, we present an efficient approach to MOX calibration using active and transfer sampling techniques coupled with non-linear machine learning algorithms, namely neural networks, …
A Land Use Regression Model For Explaining Spatial Variation In Air Pollution Levels Using A Wind Sector Based Approach, Owen Naughton, Aoife Donnelly, Paul Nolan, Francesco Pilla, Bruce Misstear, Brian Broderick
A Land Use Regression Model For Explaining Spatial Variation In Air Pollution Levels Using A Wind Sector Based Approach, Owen Naughton, Aoife Donnelly, Paul Nolan, Francesco Pilla, Bruce Misstear, Brian Broderick
Articles
Estimating pollutant concentrations at a local and regional scale is essential for good ambient air quality information in environmental and health policy decision making. Here we present a land use regression (LUR) modelling methodology that exploits the high temporal resolution of fixed-site monitoring (FSM) to produce viable air quality maps. The methodology partitions concentration time series from a national FSM network into wind-dependent sectors or “wedges”. A LUR model is derived using predictor variables calculated within the directional wind sectors, and compared against the long-term average concentrations within each sector. This study demonstrates the value of incorporating the relative position …