
Simone Alessandri'
Convolutional Networks for predicting Antimicrobial Resistance.
Rel. Giovanni Squillero, Alberto Paolo Tonda, Pietro Barbiero, Giulio Ferrero. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2021
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Abstract: |
Antibiotic resistance is a growing public health concern worldwide. Many diagnostic techniques were developed, but none of them are fast enough to predict the presence of bacteria with a resistant phenotype. This work proposes the use of a convolutional neural network on bacterial DNA sequences to predict resistance. Once the optimal neural network architecture was selected, validation was performed using a k-fold procedure estimating the loss function of both validation and test and evaluating the confusion matrix. Thanks to this technology it would be possible to speed up the choice of a proper therapeutic strategy and to avoid the rise of untreatable infection diseases. |
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Relators: | Giovanni Squillero, Alberto Paolo Tonda, Pietro Barbiero, Giulio Ferrero |
Academic year: | 2021/22 |
Publication type: | Electronic |
Number of Pages: | 111 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Biomedica |
Classe di laurea: | New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING |
Aziende collaboratrici: | UNSPECIFIED |
URI: | http://webthesis.biblio.polito.it/id/eprint/21676 |
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