Enhancing Breast Cancer Prediction with an Advanced K-Nearest Neighbors (KNN) Algorithm Integrated with Feedback Support Mechanism

Christian Arthur; Kristoko Dwi Hartomo

doi:10.1109/ICTECA60133.2023.10491036

Enhancing Breast Cancer Prediction with an Advanced K-Nearest Neighbors (KNN) Algorithm Integrated with Feedback Support Mechanism

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Christian Arthur, Kristoko Dwi Hartomo

2023 1st International Conference on Technology, Engineering, and Computing Applications: Trends in Technology Development in the Era of Society 5.0, ICTECA 2023 Conference paper Cited by 4

Abstract

Cancer poses a formidable global health challenge characterized by a persistent rise in mortality rates, with breast cancer emerging as the predominant form in 2020. Effectively addressing this heightened mortality necessitates urgent measures for early detection and timely intervention. Within the scientific landscape, numerous antecedent studies have leveraged machine learning methodologies, notably K-Nearest Neighbors (KNN) with feedback support, showcasing a substantial impact on model performance. Particularly noteworthy is the observation that for K-values exceeding 10, models incorporating feedback support demonstrated superior accuracy compared to traditional KNN approaches. Importantly, our Proposed Improved KNN introduced a noteworthy advancement, enhancing accuracy by 2.8%, from 92.3% to 95.1%. This improvement signifies a promising development in the realm of early cancer detection, highlighting the potential efficacy of our proposed approach. © 2023 IEEE.

Affiliations

Brawijaya University, Faculty of Computer Science, Malang, Indonesia; Satya Wacana Christian University, Faculty of Information Technology, Salatiga, Indonesia

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