Editorial for: “ 3D Oxygen‐Enhanced MR Imaging at 3T MR System: Comparison With Thin‐Section CT of Quantitative Capability for Pulmonary Functional Loss Assessment and Clinical Stage Classification of COPD in Smokers”

2020 ◽  
Author(s):  
Gordon W. Cowell
Keyword(s):  
Mr Imaging ◽  
Thin Section ◽  
Clinical Stage ◽  
Loss Assessment ◽  
Functional Loss ◽  
Stage Classification ◽  
3T Mr

Oxygen-enhanced MRI vs. quantitatively assessed thin-section CT: Pulmonary functional loss assessment and clinical stage classification of asthmatics

2011 ◽  
Vol 77 (1) ◽  
pp. 85-91 ◽  
Author(s):  
Yoshiharu Ohno ◽  
Hisanobu Koyama ◽  
Keiko Matsumoto ◽  
Yumiko Onishi ◽  
Munenobu Nogami ◽  
...  
Keyword(s):  
Thin Section ◽  
Clinical Stage ◽  
Loss Assessment ◽  
Functional Loss ◽  
Enhanced Mri ◽  
Stage Classification

Dynamic Oxygen-Enhanced MRI Versus Quantitative CT: Pulmonary Functional Loss Assessment and Clinical Stage Classification of Smoking-Related COPD

2008 ◽  
Vol 190 (2) ◽  
pp. W93-W99 ◽  
Author(s):  
Yoshiharu Ohno ◽  
Hisanobu Koyama ◽  
Munenobu Nogami ◽  
Daisuke Takenaka ◽  
Sumiaki Matsumoto ◽  
...  
Keyword(s):  
Clinical Stage ◽  
Loss Assessment ◽  
Quantitative Ct ◽  
Functional Loss ◽  
Enhanced Mri ◽  
Stage Classification

scholarly journals Some Problems in practice of clinical stage classification of Japan Lung Cancer Society

Haigan ◽  
1978 ◽  
Vol 18 (1) ◽  
pp. 1-5
Author(s):  
H. Homma ◽  
M. Tamura ◽  
K. Watanabe ◽  
K. Sagawa ◽  
K. Inatomi ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Stage ◽  
Cancer Society ◽  
Stage Classification

scholarly journals Assessment of Lateral Geniculate Nucleus Atrophy with 3T MR Imaging and Correlation with Clinical Stage of Glaucoma

2011 ◽  
Vol 32 (7) ◽  
pp. 1347-1353 ◽  
Author(s):  
H. Dai ◽  
K.T. Mu ◽  
J.P. Qi ◽  
C.Y. Wang ◽  
W.Z. Zhu ◽  
...  
Keyword(s):  
Mr Imaging ◽  
Lateral Geniculate Nucleus ◽  
Clinical Stage ◽  
Lateral Geniculate ◽  
3T Mr

The Value of Postoperative 3T MR Imaging Following Endoscopic Endonasal Sellar/Suprasellar Surgery

2013 ◽  
Vol 74 (S 01) ◽  
Author(s):  
Douglas Stofko ◽  
Gregory Moore ◽  
Thomas Nickles ◽  
Amir Dehdashti
Keyword(s):  
Mr Imaging ◽  
Endoscopic Endonasal ◽  
3T Mr

scholarly journals Classification of Brainwaves for Sleep Stages by High-Dimensional FFT Features from EEG Signals

2020 ◽  
Vol 10 (5) ◽  
pp. 1797 ◽  
Author(s):  
Mera Kartika Delimayanti ◽  
Bedy Purnama ◽  
Ngoc Giang Nguyen ◽  
Mohammad Reza Faisal ◽  
Kunti Robiatul Mahmudah ◽  
...  
Keyword(s):  
Machine Learning ◽  
Sleep Stage ◽  
Machine Learning Algorithms ◽  
High Dimensional ◽  
Sleep Stages ◽  
Eeg Signals ◽  
Stage Classification ◽  
Sleep Stage Classification ◽  
Low Dimensional

Manual classification of sleep stage is a time-consuming but necessary step in the diagnosis and treatment of sleep disorders, and its automation has been an area of active study. The previous works have shown that low dimensional fast Fourier transform (FFT) features and many machine learning algorithms have been applied. In this paper, we demonstrate utilization of features extracted from EEG signals via FFT to improve the performance of automated sleep stage classification through machine learning methods. Unlike previous works using FFT, we incorporated thousands of FFT features in order to classify the sleep stages into 2–6 classes. Using the expanded version of Sleep-EDF dataset with 61 recordings, our method outperformed other state-of-the art methods. This result indicates that high dimensional FFT features in combination with a simple feature selection is effective for the improvement of automated sleep stage classification.

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