Publications

Title of the publicationDate of the publicationTopic of the publicationJournals and/or open access platforms Type of audience reachedOtherREVERT partner
Towards the Interpretability of Machine Learning Predictions for Medical Applications Targeting Personalised Therapies: A Cancer Case Survey22/04/21Banegas-Luna, A.J., Pena-Garcia, J., Iftene, A., Guadagni, F., Ferroni, P., Scarpato, N., Zanzotto, F.M., Bueno-Crespo, A., Perez-Sanchez, H. 2020.

In this survey, current machine learning models, frameworks, databases and other related tools as applied to medicine - specifically, to cancer research - are analised and related interpretability, performance and the necessary input data are discussed.
Int. J. Mol. Sci. (International Journal of Molecular Sciences) large publicREVERT project acknowledgement,
https://www.mdpi.com/1422-0067/22/9/4394

Doi: 10.3390/ijms22094394
UNITOV/San Raffaele
Crack detection system in AWS Cloud using Convolutional neural networks16-18/09/2020Coca, G.L., Romanescu, S.C., Botez, S.M., Iftene, A. 2020. Crack detection system in AWS Cloud using Convolutional neural networks. In 24rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems. 16-18 September. Procedia Computer Science, vol. 176, pp. 400-409.Procedia Computer Science - Journal - Elsevierlarge publicREVERT project acknowledgement,
https://www.sciencedirect.com/science/article/pii/S1877050920318652

doi.org/10.01016/j.procs.2020.08.041
IMAGO MOL
Learn Chemistry with Augmented Reality. In 24rd International Conference on Knowledge-Based and Intellligent Information & Engineering Systems 16-18/09/2020Macariu, C., Iftene, A., Gîfu, D. 2020. Learn Chemistry with Augmented Reality. In 24rd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems. 16-18 September. Procedia Computer Science, vol. 176, pp. 2133-2142.


The purpose of this research is to demonstrate how effective these AR applications are, even that in Romania they are still in a pioneering phase.
Procedia Computer Science - Journal - Elsevierlarge publicREVERT project acknowledgement,
https://www.sciencedirect.com/science/article/pii/S1877050920321542

doi.org/10.1016/j.procs.2020.09.250
IMAGO MOL
Prehospital Cerebrovascular Accident Detection using Artificial Intelligence Powered Mobile Devices4/12/20Cristian Simionescu, Madalina Insuratelu, Robert Herscovici. (2020) Prehospital Cerebrovascular Accident Detection using Artificial Intelligence Powered Mobile Devices, Procedia Computer Science, Volume 176, 2020, Pages 2773-2782, ISSN 1877-0509,

This paper introduces Stroke Help, a mobile application utilizing various mobile technologies together with Artificial Intelligence algorithms in order to quickly detect CVA in either the user or someone the user is concerned about.
Procedia Computer Science - Journal - Elsevierlarge publicREVERT project acknowledgement,
https://www.sciencedirect.com/science/article/pii/S1877050920321839

http://doi.org/10.1016/j.procs.2020.09.279.
IMAGO MOL
Automatic Real-Time Road Crack Identification System. In 2020 22nd International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)1-4/09/2020Coca, L. G., Cușmuliuc, C. G., Morosanu, V.H., Grosu, T., Iftene, A. 2020.

In this paper are presented methods, experiments and results for detecting cracks on surfaces like streets and sidewalks.
IEEE COMP SOC
2020 22ND INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC 2020)
Book Series: International Symposium on Symbolic and Numeric Algorithms for Scientific Computing
large publicREVERT project acknowledgement,
https://ieeexplore.ieee.org/document/9357098

Doi: 10.1109/SYNASC51798.2020.00043
IMAGO-MOL
settings
Open AccessArticle
Clinical Utility of Plasma KRAS, NRAS and BRAF Mutational Analysis with Real Time PCR in Metastatic Colorectal Cancer Patients—The Importance of Tissue/Plasma Discordant Cases
29/12/2020Formica V., Lucchetti J., Doldo E., Riondino S., Morelli C., Argirò R., Renzi N., Nitti D., Nardecchia A., Dell'Aquila E., Ferroni P., Guadagni F., Palmieri G., Orlandi A., Roselli M.:

In this prospective study, the clinical utility of PL liquid biopsy for KRAS, NRAS and BRAF mutation testing in mCRC using qualitative Real Time PCR (Easy PGX) was assessed in consecutive patients with known T mutational status prior to starting a standard first-line chemotherapy.
T and PL mutation profile was compared and was evaluated whether liquid biopsy might be useful to further stratify mCRC patient prognosis and treatment response.
Journal of Clinical Medicine (JCM) – MDPI
Gold open access
large publicREVERT project acknowledgement,
https://www.mdpi.com/2077-0383/10/1/87/htm

Doi: 10.3390/jcm10010087
Unitov, San Raffaele