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Spectral data de-noising using semi-classical signal analysis: application to localized MRS
Spectral data de-noising using semi-classical signal analysis: application to localized MRS
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Spectral data de-noising using semi-classical signal analysis: application to localized MRS

Laleg-Kirati, Taous-Meriem ; Zhang, Jiayu ; Achten, Eric ; Serrai, Hacene

NMR in biomedicine, 2016-10, Vol.29 (10), p.1477-1485 [Periódico revisado por pares]

England: Blackwell Publishing Ltd

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2
Evaluation of a continuous‐time random‐walk diffusion model for the differentiation of malignant and benign breast lesions and its association with Ki‐67 expression
Evaluation of a continuous‐time random‐walk diffusion model for the differentiation of malignant and benign breast lesions and its association with Ki‐67 expression
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Evaluation of a continuous‐time random‐walk diffusion model for the differentiation of malignant and benign breast lesions and its association with Ki‐67 expression

Du, Mu ; Zou, Da ; Gao, Peng ; Yang, Zhongxian ; Hou, Yanzhen ; Zheng, Liyun ; Zhang, Na ; Liu, Yubao

NMR in biomedicine, 2023-08, Vol.36 (8), p.e4920-n/a [Periódico revisado por pares]

England: Wiley Subscription Services, Inc

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3
Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy
Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy
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Asymmetric sampling in human auditory cortex reveals spectral processing hierarchy

Giroud, Jérémy ; Trébuchon, Agnès ; Schön, Daniele ; Marquis, Patrick ; Liegeois-Chauvel, Catherine ; Poeppel, David ; Morillon, Benjamin Griffiths, Timothy D.

PLoS biology, 2020-03, Vol.18 (3), p.e3000207-e3000207 [Periódico revisado por pares]

United States: Public Library of Science

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4
Whole-genome resequencing of Dorper and Hu sheep to reveal selection signatures associated with important traits
Whole-genome resequencing of Dorper and Hu sheep to reveal selection signatures associated with important traits
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Whole-genome resequencing of Dorper and Hu sheep to reveal selection signatures associated with important traits

Lv, Xiaoyang ; Chen, Weihao ; Wang, Shanhe ; Cao, Xiukai ; Yuan, Zehu ; Getachew, Tesfaye ; Mwacharo, Joram M. ; Haile, Aynalem ; Sun, Wei

Animal biotechnology, 2023-12, Vol.34 (7), p.3016-3026 [Periódico revisado por pares]

Abingdon: Taylor & Francis

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5
Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society
Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society
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Advances in heart rate variability signal analysis: joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society

Sassi, Roberto ; Cerutti, Sergio ; Lombardi, Federico ; Malik, Marek ; Huikuri, Heikki V ; Peng, Chung-Kang ; Schmidt, Georg ; Yamamoto, Yoshiharu

Europace (London, England), 2015-09, Vol.17 (9), p.1341-1353 [Periódico revisado por pares]

England

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6
Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis
Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis
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Refined multiscale fuzzy entropy based on standard deviation for biomedical signal analysis

Azami, Hamed ; Fernández, Alberto ; Escudero, Javier

Medical & biological engineering & computing, 2017-11, Vol.55 (11), p.2037-2052 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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7
Analysis of short tandem repeat expansions and their methylation state with nanopore sequencing
Analysis of short tandem repeat expansions and their methylation state with nanopore sequencing
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Analysis of short tandem repeat expansions and their methylation state with nanopore sequencing

Giesselmann, Pay ; Brändl, Björn ; Raimondeau, Etienne ; Bowen, Rebecca ; Rohrandt, Christian ; Tandon, Rashmi ; Kretzmer, Helene ; Assum, Günter ; Galonska, Christina ; Siebert, Reiner ; Ammerpohl, Ole ; Heron, Andrew ; Schneider, Susanne A ; Ladewig, Julia ; Koch, Philipp ; Schuldt, Bernhard M ; Graham, James E ; Meissner, Alexander ; Müller, Franz-Josef

Nature biotechnology, 2019-12, Vol.37 (12), p.1478-1481 [Periódico revisado por pares]

United States: Nature Publishing Group

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8
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
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Arrhythmia detection using deep convolutional neural network with long duration ECG signals

Yıldırım, Özal ; Pławiak, Paweł ; Tan, Ru-San ; Acharya, U. Rajendra

Computers in biology and medicine, 2018-11, Vol.102, p.411-420 [Periódico revisado por pares]

United States: Elsevier Ltd

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9
Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals
Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals
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Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals

Malan, Nitesh Singh ; Sharma, Shiru

Computers in biology and medicine, 2019-04, Vol.107, p.118-126 [Periódico revisado por pares]

United States: Elsevier Ltd

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10
Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals
Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals
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Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals

Yildirim, Ozal ; Talo, Muhammed ; Ay, Betul ; Baloglu, Ulas Baran ; Aydin, Galip ; Acharya, U. Rajendra

Computers in biology and medicine, 2019-10, Vol.113, p.103387-103387, Article 103387 [Periódico revisado por pares]

United States: Elsevier Ltd

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