Breast cancer detection by leveraging Machine Learning

被引：38

作者：

Vaka, Anji Reddy ^{[1
]}

Soni, Badal ^{[1
]}

Reddy, Sudheer K.

机构：

[1] Natl Inst Technol, Dept CSE, Silchar, India

来源：

ICT EXPRESS | 2020年 / 6卷 / 04期

关键词：

Machine Learning; Classification; Breast cancer; Deep learning;

D O I：

10.1016/j.icte.2020.04.009

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

India has witnessed 30% of the cases of breast cancer during the last few years and it is likely to increase. Breast cancer in India accounts that one woman is diagnosed every two minutes and every nine minutes, one woman dies. Early detection and diagnosis can save the lives of cancer patients. This paper presents a novel method to detect breast cancer by employing techniques of Machine Learning. The authors carried out an experimental analysis on a dataset to evaluate the performance. The proposed method has produced highly accurate and efficient results when compared to the existing methods. (C) 2020 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V.

引用

页码：320 / 324

页数：5

共 50 条

[21] Machine Learning Techniques for Breast Cancer Detection
Hall, Karl
Chang, Victor
Mitchell, Paul
PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON COMPLEXITY, FUTURE INFORMATION SYSTEMS AND RISK (COMPLEXIS), 2022, : 116 - 122
[22] Cancer detection and segmentation using machine learning and deep learning techniques: a review
Rai, Hari Mohan
MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (09) : 27001 - 27035
[23] Breast cancer detection based on Gabor-wavelet transform and machine learning methods
Ghasemzadeh, Ardalan
Azad, Saeed Sarbazi
Esmaeili, Elham
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2019, 10 (07) : 1603 - 1612
[24] Breast cancer detection based on Gabor-wavelet transform and machine learning methods
Ardalan Ghasemzadeh
Saeed Sarbazi Azad
Elham Esmaeili
International Journal of Machine Learning and Cybernetics, 2019, 10 : 1603 - 1612
[25] Comparison of Machine Learning Classifiers for the Detection of Breast Cancer in an Electrical Impedance Tomography Setup
Rixen, Joeran
Blass, Nico
Lyra, Simon
Leonhardt, Steffen
ALGORITHMS, 2023, 16 (11)
[26] Machine Learning Classifiers on Breast Cancer Recurrences
Magboo, Vincent Peter C.
Magboo, Ma Sheila A.
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021), 2021, 192 : 2742 - 2752
[27] Comparing the Performance of Various Supervised Machine Learning Techniques for Early Detection of Breast Cancer
Abiodun, Moses Kazeem
Misra, Sanjay
Awotunde, Joseph Bamidele
Adewole, Samson
Joshua, Akor
Oluranti, Jonathan
HYBRID INTELLIGENT SYSTEMS, HIS 2021, 2022, 420 : 473 - 482
[28] A Review of Machine Learning Techniques for the Classification and Detection of Breast Cancer from Medical Images
Jalloul, Reem
Chethan, H. K.
Alkhatib, Ramez
DIAGNOSTICS, 2023, 13 (14)
[29] Breast cancer outcome prediction with tumour tissue images and machine learning
Turkki, Riku
Byckhov, Dmitrii
Lundin, Mikael
Isola, Jorma
Nordling, Stig
Kovanen, Panu E.
Verrill, Clare
von Smitten, Karl
Joensuu, Heikki
Lundin, Johan
Linder, Nina
BREAST CANCER RESEARCH AND TREATMENT, 2019, 177 (01) : 41 - 52
[30] Comparative analysis of breast cancer detection using machine learning and biosensors
Amethiya, Yash
Pipariya, Prince
Patel, Shlok
Shah, Manan
INTELLIGENT MEDICINE, 2022, 2 (02): : 69 - 81

← 1 2 3 4 5 →