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On Cervical Cancer Diagnostics Using Machine Learning (CROSBI ID 719120)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Glučina, Matko ; Lorencin, Ariana ; Lorencin, Ivan On Cervical Cancer Diagnostics Using Machine Learning // RI-STEM proceedings. 2022. str. 19-22

Podaci o odgovornosti

Glučina, Matko ; Lorencin, Ariana ; Lorencin, Ivan

engleski

On Cervical Cancer Diagnostics Using Machine Learning

This paper presents the classification of cervical cancer using the Multilayer Perceptron into a publicly available dataset Cervical cancer (Risk Factors) taken from the UCI Machine learning repository consisting of 36 attributes with 859 instances. The target values were Hinselmann, Schiller, Cytology, and biopsy by processing the dataset and using the GridSearch method, the MLP algorithm gives a high percentage of accuracy for all four outputs, but an insight into other metrics shows that additional research elaboration is needed. based on the f1 score the best result for Hinselmann is 0.17, Schiller in the amount of 0.4, Cytology 0.29, and Biopsy 0.19 which indicates more than enough of a poor-quality model for implementation in real conditions.

Artificial intelligence ; Cervical cancer ; Machine learning ; Multilayer perceptron ; Neurons

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Podaci o prilogu

19-22.

2022.

objavljeno

Podaci o matičnoj publikaciji

RI-STEM proceedings

Podaci o skupu

International Student Scientific Conference (Ri-STEM 2022)

predavanje

08.06.2022-09.06.2022

Rijeka, Hrvatska

Povezanost rada

Interdisciplinarne tehničke znanosti, Računarstvo, Temeljne medicinske znanosti