Early predictive model for breast cancer classification using blended ensemble learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Strategy and Management,Safety, Risk, Reliability and Quality
Link
https://link.springer.com/content/pdf/10.1007/s13198-022-01696-0.pdf
Reference27 articles.
1. Agarap AFM (2018) [ACM Press the 2nd international conference—Phu Quoc Island, Viet Nam (2018.02.02–2018.02.04)] Proceedings of the 2nd international conference on machine learning and soft computing—ICMLSC '18—“On breast cancer detection”, pp 5–9
2. Akbugday B (2019) 2019 Medical Technologies Congress (TIPTEKNO)—Izmir, Turkey (2019.10.3–2019.10.5)] 2019 Medical Technologies Congress (TIPTEKNO)—“Classification of Breast Cancer Data Using Machine Learning Algorithms”, pp 1–4
3. Aslan MF, Celik Y, Sabanci K, Durdu A (2018) Breast cancer diagnosis by different machine learning methods using blood analysis data. Int J Intell Syst Appl Eng 6(4):289–293
4. Asri H, Mousannif H, Al Moatassime H, Noel T (2016) Using machine learning algorithms for breast cancer risk prediction and diagnosis. Procedia Comput Sci 83:1064–1069
5. Assiri AS, Nazir S, Velastin SA (2020) Breast tumor classification using an ensemble machine learning method. J Imaging 6(6):39
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