Results 201 to 210 of about 265,861 (250)

Segmenting Older Adults by Their Acceptance of Digital Health Care Devices: Cross-Sectional Study Using the Augmented Technology Acceptance Model and K-Means Clustering. [PDF]

JMIR Form Res
Koo T, Jo IH, Pyun DY, Yoo J.
europepmc   +1 more source

Assessment of cardiac allograft vasculopathy in heart transplant patients using multidimensional dynamic CTA and principal components analysis. [PDF]

BMC Med Imaging
Zhang X, Yang M, Huang T, Qin Q, Qian P, Luo Y, Wang J.   +6 more
europepmc   +1 more source

Vibrational spectroscopic characterisation of fluorescent-protein-tagged and wild-type bacteria in surface-associated microdroplets.

Faraday Discuss
Lima C, Allkja J, Raval R.
europepmc   +1 more source

Cervical cancer perceived behavioral risk factors using logistic regression technique. [PDF]

J Biomed Res
Elzein IM, Chamseddine A, Eltanboly A, Elzein A.   +3 more
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Winter Temperature and Long-Term Mortality After Coronary Artery Bypass Grafting: A Multicenter Cohort Study. [PDF]

J Clin Med
Urbanowicz T, Aboul-Hassan SS, Skotak K, Luszczyn M, Moskal Ł, Bratkowski J, Bartkowski J, Perek B, Wilczyński M, Filipiak KJ, Cichoń R, Jemielity M.   +11 more
europepmc   +1 more source

Global patterns and inequalities in healthy aging: a multidimensional analysis using composite index and explainable AI. [PDF]

Front Public Health
Çelik S, Köroğlu CZ.
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Principal Component Analysis (PCA)

exaly   +5 more sources

PCA-Pruner: Filter pruning by principal component analysis

Journal of Intelligent & Fuzzy Systems, 2022
Deep Convolutional Neural Networks (CNNs) have been widely used in various domains due to their outstanding performance. However, they simultaneously bring enormous computational overhead, making it difficult to deploy to mobile and edge devices. Therefore, researchers use network compression techniques such as quantization, knowledge distillation and ...
Wei Zhang, Zhiming Wang
openaire   +1 more source

Principal components analysis (PCA)

Computers & Geosciences, 1993
Principal Components Analysis (PCA) as a method of multivariate statistics was created before the Second World War. However, the wider application of this method only occurred in the 1960s, during the “Quantitative Revolution” in the Natural and Social Sciences.
Andrzej Maćkiewicz, Waldemar Ratajczak
openaire   +1 more source