Exploring Cosine and Euclidean Metrics in K-Nearest Neighbors for Breast Cancer Diagnosis-Reference-Cited by-同舟云学术

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Exploring Cosine and Euclidean Metrics in K-Nearest Neighbors for Breast Cancer Diagnosis

Published:2024-07-17 Issue: Volume:71 Page:330-335
ISSN:
Container-title:2024 7th International Conference on Informatics and Computational Sciences (ICICoS)
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Author:

Prasetyo Simeon Yuda¹,Nabiilah Ghinaa Zain¹,Sihotang Erna Fransisca Angela²,Minor Kelvin Asclepius³

Affiliation:

1. Bina Nusantara University,School of Computer Science,Computer Science Department,Jakarta,Indonesia,11480

2. Bina Nusantara University,School of Computer Science,Statistics Department,Jakarta,Indonesia,11480

3. Bina Nusantara University,School of Computer Science,Mathematics Department,Jakarta,Indonesia,11480

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10636850/10636819/10636883.pdf?arnumber=10636883

Reference23 articles.

1. A single-cell and spatially resolved atlas of human breast cancers

2. Prediction of Breast Cancer, Comparative Review of Machine Learning Techniques, and Their Analysis

3. Breast Cancer—Epidemiology, Risk Factors, Classification, Prognostic Markers, and Current Treatment Strategies—An Updated Review

4. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries;Sung;CA Cancer J Clin,2021

5. Age-Dependent Causes of Death among Patients with Breast Cancer Based on Osaka Cancer Registry and Vital Statistics in Japan

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