Comparison of Deep Learning and Machine Learning Algorithms to Diagnose and Predict Breast Cancer

被引：0

作者：

Ghazalnaz Sharifonnasabi, F. ^{[1
]}

Makhdoom, Iman ^{[2
]}

机构：

[1] School of Science and Technology, James Cook University, Singapore,387380, Singapore

[2] Department of Statistics, Payame Noor University (PNU), P.O.Box 19395-4697, Tehran, Iran

来源：

Lecture Notes in Networks and Systems | 2024年 / 839卷

关键词：

D O I：

暂无

中图分类号：

学科分类号：

摘要：

Adaptive boosting - Barium compounds - Convolution - Convolutional neural networks - Decision trees - Deep learning - Diagnosis - Diseases - Forecasting - Nearest neighbor search - Support vector machines

引用

页码：31 / 43

共 39 条

[31] Effectiveness of data-driven wind turbine wake models developed by machine/deep learning with spatial-segmentation technique
Wang, Longyan
Xie, Junhang
Luo, Wei
Wang, Zilu
Zhang, Bowen
Chen, Meng
Tan, Andy C.C.
Sustainable Energy Technologies and Assessments, 2022, 53
[32] An Extensive Review on Lung Cancer Diagnosis Using Machine Learning Techniques on Radiological Data: State-of-the-art and Perspectives
Shah, Syed Naseer Ahmad
Parveen, Rafat
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING, 2023, 30 (08) : 4917 - 4930
[33] CT-based Machine Learning Model of Different Phases to Predict WHO/ISUP Nuclear Grade of Clear-Cell Renal Cell Carcinoma
Han, Jiamin
Xia, Yangyang
Chen, Wei
Qiao, Xu
Jiang, Xuewen
Gao, Rui
ACM International Conference Proceeding Series, 2022, : 83 - 88
[34] Performance Deterioration of Deep Learning Models after Clinical Deployment: A Case Study with Auto-segmentation for Definitive Prostate Cancer Radiotherapy
Wang, Biling
Dohopolski, Michael
Bai, Ti
Wu, Junjie
Hannan, Raquibul
Desai, Neil
Garant, Aurelie
Yang, Daniel
Nguyen, Dan
Lin, Mu-Han
Timmerman, Robert
Wang, Xinlei
Jiang, Steve
arXiv, 2022,
[35] Development and Validation of a Machine Learning Model for Predicting the Prognosis of Older Patients with Gastric Cancer: A Retrospective, Population-Based Cohort Study In China
Huang, Ze-Ning
Zhang, Xing-Qi
Wu, Ju
Zheng, Chang-Yue
Xie, Rong-Zhen
Wu, Ying-Xin
Liu, Xiao-Dong
Chen, Qi-Yue
Xie, Jian-Wei
Li, Ping
Zheng, Chao-Hui
Lin, Jian-Xian
Zhou, Yanbing
Huang, Chang-Ming
SSRN,
[36] Retraction note: Classification of stroke disease using machine learning algorithms (Neural Computing and Applications, (2020), 32, 3, (817-828), 10.1007/s00521-019-04041-y)
Govindarajan, Priya
Soundarapandian, Ravichandran Kattur
Gandomi, Amir H.
Patan, Rizwan
Jayaraman, Premaladha
Manikandan, Ramachandran
Neural Computing and Applications, 2024,
[37] Retraction Note: Design and application of optical communication technology based on machine learning algorithms in physical education teaching information management system (Optical and Quantum Electronics, (2024), 56, 1, (111), 10.1007/s11082-023-05717-5)
Zhai, Qingwen
Chen, Xiao
Optical and Quantum Electronics, 56 (10):
[38] Retraction Note: Carbon pattern in polymeric nanofabrication for breast tumor molecular cell analysis using hybrid machine learning technique (Optical and Quantum Electronics, (2023), 55, 10, (919), 10.1007/s11082-023-05142-8)
Kiran, K.S.
Kumar, Gajendra
Bhagat, Akash Kumar
Vekariya, Daxa
Sharma, Deeplata
Rajput, Mukesh
Sharma, Meenakshi
Optical and Quantum Electronics, 56 (10):
[39] Retraction Note: How Have the COVID-19 Pandemic and Market Sentiment Affected the FX Market? Evidence from Statistical Models and Deep Learning Algorithms (International Journal of Computational Intelligence Systems, (2023), 16, 1, (19), 10.1007/s44196-023-00194-w)
Luo, Hang
Luo, Xiaoyu
Gu, Shuhao
International Journal of Computational Intelligence Systems, 17 (01):

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