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Pregled bibliografske jedinice broj: 1182758

URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES


Lorencin, Ivan; Baressi Šegota, Sandi; Anđelić, Nikola; Mrzljak, Vedran; Smolić, Klara; Španjol, Josip; Car, Zlatan
URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES // World of health, 4 (2022), 64-69 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 1182758 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES

Autori
Lorencin, Ivan ; Baressi Šegota, Sandi ; Anđelić, Nikola ; Mrzljak, Vedran ; Smolić, Klara ; Španjol, Josip ; Car, Zlatan

Izvornik
World of health (2623-5773) 4 (2022); 64-69

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
AI ; CNN ; Urinary Bladder Cancer

Sažetak
Bladder cancer is one of the most common malignancies in men in Croatia. It is characterized by a high recurrence rate and high metastatic potential. For this reason, accurate and timely diagnosis is needed in order to treat bladder cancer as successfully as possible. Cystoscopy as a diagnostic method shows poorer accuracy of Carcinoma in situ (CIS) diagnosis, where every fourth CIS remains undiagnosed. For this reason, the artificial intelligence-based approach is proposed. The standard approach to image classification is utilization of convolutional neural networks (CNN). Literature overview shows a possibility of using pre-defined CNN models, such as VGG-16. VGG- 16, in this case, needs to be customized in order to adapt it to four-class classification problem. By using a customized VGG-16 model, high classification performances are achieved. When AdaGrad and AdaMax solvers are used, AUC micro values up to 0.98 are achieved.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti, Temeljne medicinske znanosti, Kliničke medicinske znanosti



POVEZANOST RADA


Projekti:
Ostalo-CEI - 305.6019-20 - Use of regressive artificial intelligence (AI) and machine learning (ML) methods in modelling of COVID-19 spread (COVIDAi) (Car, Zlatan, Ostalo - CEI Extraordinary Call for Proposals 2020) ( POIROT)
NadSve-Sveučilište u Rijeci-uniri-tehnic-18-275-1447 - Razvoj inteligentnog ekspertnog sustava za online diagnostiku raka mokračnog mjehura (Car, Zlatan, NadSve - UNIRI potpore) ( POIROT)
EK-KF-KK.01.1.1.01.0009-2 - Napredne metode i tehnologije u znanosti o podatcima i kooperativnim sustavima - IJ za napredne kooperativne sustave (DATACROSS) (Petrović, Ivan; Šmuc, Tomislav, EK - KK.01.1.1.01) ( POIROT)
EK-EFRR-KK.01.2.2.03.0004 - Centar kompetencija za pametne gradove (CEKOM) (Car, Zlatan; Slavić, Nataša; Vilke, Siniša, EK - KK.01.2.2.03) ( POIROT)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada www.fzsri.uniri.hr

Citiraj ovu publikaciju:

Lorencin, Ivan; Baressi Šegota, Sandi; Anđelić, Nikola; Mrzljak, Vedran; Smolić, Klara; Španjol, Josip; Car, Zlatan
URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES // World of health, 4 (2022), 64-69 (međunarodna recenzija, članak, znanstveni)
Lorencin, I., Baressi Šegota, S., Anđelić, N., Mrzljak, V., Smolić, K., Španjol, J. & Car, Z. (2022) URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES. World of health, 4, 64-69.
@article{article, author = {Lorencin, Ivan and Baressi \v{S}egota, Sandi and An\djeli\'{c}, Nikola and Mrzljak, Vedran and Smoli\'{c}, Klara and \v{S}panjol, Josip and Car, Zlatan}, year = {2022}, pages = {64-69}, keywords = {AI, CNN, Urinary Bladder Cancer}, journal = {World of health}, volume = {4}, issn = {2623-5773}, title = {URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES}, keyword = {AI, CNN, Urinary Bladder Cancer} }
@article{article, author = {Lorencin, Ivan and Baressi \v{S}egota, Sandi and An\djeli\'{c}, Nikola and Mrzljak, Vedran and Smoli\'{c}, Klara and \v{S}panjol, Josip and Car, Zlatan}, year = {2022}, pages = {64-69}, keywords = {AI, CNN, Urinary Bladder Cancer}, journal = {World of health}, volume = {4}, issn = {2623-5773}, title = {URINARY BLADDER CANCER DIAGNOSIS USING CUSTOMIZED VGG-16 ARCHITECTURES}, keyword = {AI, CNN, Urinary Bladder Cancer} }




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