Eosinophilic phenotype classification of patients with asthma and/or COPD in NOVELTY

2021 ◽  
Author(s):  
David Price ◽  
Ian D Pavord ◽  
Keith Peres Da Costa ◽  
Alvar Agustí ◽  
Gary P Anderson ◽  
...  
Keyword(s):  
Phenotype Classification

scholarly journals Phenotype classification of zebrafish embryos by supervised learning

2012 ◽  
Vol 211 ◽  
pp. S152 ◽  
Author(s):  
Nathalie Jeanray ◽  
Raphaël Marée ◽  
Benoist Pruvot ◽  
Olivier Stern ◽  
Pierre Geurts ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Zebrafish Embryos ◽  
Phenotype Classification

scholarly journals Long term EIT based compliance monitoring in COVID-19 patients

2021 ◽  
Vol 7 (2) ◽  
pp. 323-326
Author(s):  
Imanol Isasa Reinoso ◽  
Rongqing Chen ◽  
András Lovas ◽  
Knut Moeller
Keyword(s):  
Electrical Impedance ◽  
Disease Diagnosis ◽  
The Body ◽  
Respiratory Complications ◽  
Impedance Tomography ◽  
Non Invasive ◽  
Phenotype Classification ◽  
Continuous Technology

Abstract The COVID-19 is a viral infection that causes respiratory complications. Infected lungs often present ground glass opacities, thus suggesting that medical imaging technologies could provide useful information for the disease diagnosis, treatment, and posterior recovery. The Electrical Impedance Tomography (EIT) is a non-invasive, radiationfree, and continuous technology that generates images by using a sequence of current injections and voltage measurements around the body, making it very appropriate for the study to monitor the regional behaviour of the lung. Moreover, this tool could also be used for a preliminary COVID-19 phenotype classification of the patients. This study is based on the monitoring of lung compliances of two COVID-19-infected patients: the results indicate that one of them could belong to the H-type, while the other is speculated belongs to L-type. It has been concluded that the EIT is a useful tool to obtain information regarding COVID-19 patients and could also be used to classify different phenotypes.

scholarly journals Phenotype Classification of Zebrafish Embryos by Supervised Learning

PLoS ONE ◽  
2015 ◽  
Vol 10 (1) ◽  
pp. e0116989 ◽  
Author(s):  
Nathalie Jeanray ◽  
Raphaël Marée ◽  
Benoist Pruvot ◽  
Olivier Stern ◽  
Pierre Geurts ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Zebrafish Embryos ◽  
Phenotype Classification

scholarly journals Molecular classification of urothelial carcinoma: global mRNA classification versus tumour-cell phenotype classification

2017 ◽  
Vol 242 (1) ◽  
pp. 113-125 ◽  
Author(s):  
Gottfrid Sjödahl ◽  
Pontus Eriksson ◽  
Fredrik Liedberg ◽  
Mattias Höglund
Keyword(s):  
Urothelial Carcinoma ◽  
Tumour Cell ◽  
Molecular Classification ◽  
Cell Phenotype ◽  
Phenotype Classification
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