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Published in 2018 at "European Radiology"
DOI: 10.1007/s00330-018-5563-3
Abstract: ObjectivesThe purpose of this study was to investigate which feature of the breast-specific gamma imaging (BSGI) uptake in women who were recently diagnosed with breast cancer was associated with malignancy.MethodsData on 231 newly diagnosed breast…
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Keywords:
malignancy;
feature analysis;
mass;
breast ... See more keywords
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Published in 2018 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-018-5638-9
Abstract: Falls are reported to be the leading causes of accidental deaths among elderly people. Automatic detection of falls from video sequences is an assistant technology for low-cost health care systems. In this paper, we present…
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Keywords:
feature analysis;
slow feature;
feature;
fall detection ... See more keywords
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Published in 2024 at "Journal of Neuro-Oncology"
DOI: 10.1007/s11060-024-04725-z
Abstract: Quantifying tumor growth and treatment response noninvasively poses a challenge to all experimental tumor models. The aim of our study was, to assess the value of quantitative and visual examination and radiomic feature analysis of…
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Keywords:
mice;
feature analysis;
tcp tcp;
analysis ... See more keywords
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Published in 2017 at "Journal of Mountain Science"
DOI: 10.1007/s11629-017-4497-6
Abstract: The fund name “National Key Technologies R&D Program of China” in the section of “Acknowledgements” is incorrect.The correct fund name is “National Key Research and Development Program of China”.
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Keywords:
erratum geometrical;
feature analysis;
assessment xinmo;
analysis disaster ... See more keywords
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Published in 2018 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2018.09.331
Abstract: Abstract Slow feature analysis has proven to be an effective process monitoring and fault diagnosis approach. By isolating temporal behaviors from steady-state variations in process data, slow feature analysis enables a concurrent monitoring of operating…
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Keywords:
process;
feature analysis;
slow feature;
order ... See more keywords
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Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.08.067
Abstract: Abstract Slow Feature Analysis (SFA) is an unsupervised learning algorithm which extracts slowly varying features from a temporal vectorial signal. In SFA, feature slowness is measured by the average value of its squared time-derivative. In…
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Keywords:
feature analysis;
feature;
frequency;
slow feature ... See more keywords
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Published in 2024 at "Analytical Chemistry"
DOI: 10.1021/acs.analchem.4c02329
Abstract: Interpretability is just as important as accuracy when it comes to complex models, especially in the context of deep learning models. Explainable artificial intelligence (XAI) approaches have been developed to address this problem. The literature…
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Keywords:
deep learning;
feature analysis;
learning models;
spectral zones ... See more keywords
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Published in 2020 at "Industrial & Engineering Chemistry Research"
DOI: 10.1021/acs.iecr.9b05547
Abstract: Slow feature analysis (SFA) has been extensively adopted for process monitoring. Since the prominent ability of exploring dynamic information of the industrial process, SFA could monitor the proces...
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Keywords:
feature analysis;
slow feature;
concurrent monitoring;
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Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.1c06649
Abstract: Independent component analysis (ICA) is an excellent latent variables (LVs) extraction method that can maximize the non-Gaussianity between LVs to extract statistically independent latent variables and which has been widely used in multivariate statistical process…
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Keywords:
slow feature;
fault detection;
feature analysis;
detection ... See more keywords
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Published in 2019 at "Earth and Space Science"
DOI: 10.1029/2018ea000514
Abstract: Feature analysis of weak nonlinear signals from geographic spatiotemporal data has received increasing attention. Most existing signal processing methods cannot effectively perform comprehensive feature analysis because of the multiple dimensions and unbalance of spatiotemporal data.…
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Keywords:
spatiotemporal data;
multidimensional feature;
feature;
feature analysis ... See more keywords
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Published in 2025 at "Current opinion in pediatrics"
DOI: 10.1097/mop.0000000000001487
Abstract: PURPOSE OF REVIEW This review highlights recent developments in the use of machine learning supported facial feature analysis in the context of genetic and syndromic conditions. The review focusses on 2D image-based tools. The 2D…
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Keywords:
genetics;
feature analysis;
medical genetics;
analysis ... See more keywords