A META-HEURISTIC MULTI-OBJECTIVE APPROACH TO THE MODEL SELECTION OF CONVOLUTION NEURAL NETWORKS FOR URINARY BLADDER CANCER DIAGNOSIS (CROSBI ID 709585)
Prilog sa skupa u zborniku | ostalo | međunarodna recenzija
Podaci o odgovornosti
Lorencin, Ivan ; Smolić, Klara ; Markić, Dean ; Španjol, Josip
engleski
A META-HEURISTIC MULTI-OBJECTIVE APPROACH TO THE MODEL SELECTION OF CONVOLUTION NEURAL NETWORKS FOR URINARY BLADDER CANCER DIAGNOSIS
Bladder cancer is one of the most common malignancies of the urinary tract. It is characterized by high metastatic potential and a high recurrence rate, which significantly complicates diagnosis and treatment. In order to increase the accuracy of the diagnostic procedure, algorithms based on artificial intelligence are introduced. This paper presents the principle of selection of convolutional neural network (CNN) models based on a multi- objective approach that maximizes classification and generalization performance. Model selection is performed on two standard CNN architectures, AlexNet and VGG-16. Classification performances are measured by using ROC analysis and the resulting AUC value. On the other hand, generalization performances are evaluated by using a 5- fold cross-validation procedure. By using these two metrics, a multi-objective fitness function, used in meta-heuristic algorithms, is designed. The multi-objective search was performed using a Genetic algorithm (GA) and a Discrete Particle Swarm (D-PS) algorithm. From obtained results, it can be noticed that such an approach has resulted in CNN models that are defined with high classification and generalization performances. When a GA-based approach is used, fitness values up to 0.97 are achieved. On the other hand, by using the D-PS approach, fitness values up to 0.99 are achieved pointing towards the conclusion that such an approach has provided models with higher classification and generalization performances.
Convolutional neural network, Discrete particle swarm algorithm, Genetic algorithm, Urinary bladder cancer
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Podaci o prilogu
1-4.
2021.
objavljeno
Podaci o matičnoj publikaciji
1st International Conference on Chemo and Bioinformatics
Kragujevac:
Podaci o skupu
1st International Conference on Chemo and BioInformatics (ICCBIKG 2021)
predavanje
26.10.2021-27.10.2021
Kragujevac, Srbija