Imperial College London
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Riccardo Secoli, PhD, MBA

Faculty of Engineering, Department of Mechanical Engineering

Honorary Research Associate
 
 
 
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Contact

 

+44 (0)20 7594 3667r.secoli Website

 
 
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Location

 

414ABessemer BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Riva:2021:10.3390/cancers13051073,
author = {Riva, M and Sciortino, T and Secoli, R and D'Amico, E and Moccia, S and Fernandes, B and Conti, Nibali M and Gay, L and Rossi, M and De, Momi E and Bello, L},
doi = {10.3390/cancers13051073},
journal = {CANCERS},
title = {Glioma <i>biopsies</i> Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples},
url = {http://dx.doi.org/10.3390/cancers13051073},
volume = {13},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AU  - Riva,M
AU  - Sciortino,T
AU  - Secoli,R
AU  - D'Amico,E
AU  - Moccia,S
AU  - Fernandes,B
AU  - Conti,Nibali M
AU  - Gay,L
AU  - Rossi,M
AU  - De,Momi E
AU  - Bello,L
DO  - 10.3390/cancers13051073
PY  - 2021///
TI  - Glioma <i>biopsies</i> Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples
T2  - CANCERS
UR  - http://dx.doi.org/10.3390/cancers13051073
UR  - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000627944600001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a2bf6146997ec60c407a63945d4e92bb
VL  - 13
ER  -
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