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Journals / Sakarya University Journal of Computer and Information Sciences / 2026 / Volume: 3 Issue: 2

Detection of Cervix Cancer from Pap-smear Images

Fatma Betül Akyol(YILDIZ TEKNİK ÜNİVERSİTESİ)0000-0002-3836-1317
Oğuz Altun(YILDIZ TEKNİK ÜNİVERSİTESİ)0000-0001-8823-3148
Pages
—
Publication Date
2020-08-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Support Vector Machines (SVM), Naive Bayes, Random Forest (RF), Multilayer Perceptron (MLP), Logistic Regression (LR), K- Nearest Neighbor (KNN) methods were applied to the created dataset, and accuracy values between 83% and 92% were obtained.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Pap-smear test is used to detect cervical cancer, which ranks fourth in the ranking of cancer diseases in women worldwide.
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Key Findings & Data:For each of the 917 images in the Herlev dataset, these features were extracted and stored in a dataset.
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Conclusion & Impact:Support Vector Machines (SVM), Naive Bayes, Random Forest (RF), Multilayer Perceptron (MLP), Logistic Regression (LR), K- Nearest Neighbor (KNN) methods were applied to the created dataset, and accuracy values between 83% and 92% were obtained.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Cervical cancer · Pap-smear · Segmentation

Abstract

Pap-smear test is used to detect cervical cancer, which ranks fourth in the ranking of cancer diseases in women worldwide. In this study, it is aimed to design a computer based decision system that can detect cervical cancer at an early stage. Normal and abnormal cells are found in the cervix images obtained as a result of the pap-smear test and the abnormal cells are marked on the image. The features extracted from the images were examined with pathologists and a dataset was created. For each of the 917 images in the Herlev dataset, these features were extracted and stored in a dataset. Support Vector Machines (SVM), Naive Bayes, Random Forest (RF), Multilayer Perceptron (MLP), Logistic Regression (LR), K- Nearest Neighbor (KNN) methods were applied to the created dataset, and accuracy values between 83% and 92% were obtained.

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Cite This Article

Akyol, F. B., Altun, O. (2020). Detection of Cervix Cancer from Pap-smear Images. Sakarya University Journal of Computer and Information Sciences, Volume: 3 Issue: 2. https://doi.org/10.35377/saucis.03.02.722670

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