Explainable Ensemble Machine Learning for Breast Cancer Diagnosis Based on Ultrasound Image Texture Features
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Sun, Xiaolei & Liu, Mingxi & Sima, Zeqian, 2020. "A novel cryptocurrency price trend forecasting model based on LightGBM," Finance Research Letters, Elsevier, vol. 32(C).
- Mukund Sundararajan & Amir Najmi, 2019. "The many Shapley values for model explanation," Papers 1908.08474, arXiv.org, revised Feb 2020.
- Alireza Rezazadeh, 2020. "A Generalized Flow for B2B Sales Predictive Modeling: An Azure Machine-Learning Approach," Forecasting, MDPI, vol. 2(3), pages 1-17, August.
- Davide Castelvecchi, 2016. "Can we open the black box of AI?," Nature, Nature, vol. 538(7623), pages 20-23, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Yamashiro, Hirochika & Nonaka, Hirofumi, 2021. "Estimation of processing time using machine learning and real factory data for optimization of parallel machine scheduling problem," Operations Research Perspectives, Elsevier, vol. 8(C).
- Sonia Leva, 2021. "Editorial for Special Issue: “Feature Papers of Forecasting”," Forecasting, MDPI, vol. 3(1), pages 1-3, February.
- Hugh Chen & Scott M. Lundberg & Su-In Lee, 2022. "Explaining a series of models by propagating Shapley values," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
- Laith T. Khrais, 2020. "Role of Artificial Intelligence in Shaping Consumer Demand in E-Commerce," Future Internet, MDPI, vol. 12(12), pages 1-14, December.
- Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.
- Wenguang Zhang & Ting Lei & Yu Gong & Jun Zhang & Yirong Wu, 2022. "Using Explainable Artificial Intelligence to Identify Key Characteristics of Deep Poverty for Each Household," Sustainability, MDPI, vol. 14(16), pages 1-21, August.
- Masayoshi Mase & Art B. Owen & Benjamin B. Seiler, 2022. "Variable importance without impossible data," Papers 2205.15750, arXiv.org, revised Apr 2023.
- Hakan Pabuccu & Adrian Barbu, 2023. "Feature Selection with Annealing for Forecasting Financial Time Series," Papers 2303.02223, arXiv.org, revised Feb 2024.
- Eduardo Graells-Garrido & Vanessa Peña-Araya & Loreto Bravo, 2020. "Adoption-Driven Data Science for Transportation Planning: Methodology, Case Study, and Lessons Learned," Sustainability, MDPI, vol. 12(15), pages 1-17, July.
- Kumar, Rishabh & Koshiyama, Adriano & da Costa, Kleyton & Kingsman, Nigel & Tewarrie, Marvin & Kazim, Emre & Roy, Arunita & Treleaven, Philip & Lovell, Zac, 2023. "Deep learning model fragility and implications for financial stability and regulation," Bank of England working papers 1038, Bank of England.
- Jinxin Wang & Chaoran Gao & Manman Wang & Yan Zhang, 2023. "Identification of Urban Functional Areas and Urban Spatial Structure Analysis by Fusing Multi-Source Data Features: A Case Study of Zhengzhou, China," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
- Helder Sebastião & Pedro Godinho, 2021. "Forecasting and trading cryptocurrencies with machine learning under changing market conditions," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
- Chenfeng Yan & Quan Chen & Xinyue Zhou & Xin Dai & Zhilin Yang, 2024. "When the Automated fire Backfires: The Adoption of Algorithm-based HR Decision-making Could Induce Consumer’s Unfavorable Ethicality Inferences of the Company," Journal of Business Ethics, Springer, vol. 190(4), pages 841-859, April.
- Bouri, Elie & Christou, Christina & Gupta, Rangan, 2022.
"Forecasting returns of major cryptocurrencies: Evidence from regime-switching factor models,"
Finance Research Letters, Elsevier, vol. 49(C).
- Elie Bouri & Christina Christou & Rangan Gupta, 2022. "Forecasting Returns of Major Cryptocurrencies: Evidence from Regime-Switching Factor Models," Working Papers 202213, University of Pretoria, Department of Economics.
- Brian G Booth & Eva Hoefnagels & Toon Huysmans & Jan Sijbers & Noël L W Keijsers, 2020. "PAPPI: Personalized analysis of plantar pressure images using statistical modelling and parametric mapping," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-22, February.
- Shuo Sun & Rundong Wang & Bo An, 2021. "Reinforcement Learning for Quantitative Trading," Papers 2109.13851, arXiv.org.
- O’Dwyer, Edward & Pan, Indranil & Acha, Salvador & Shah, Nilay, 2019. "Smart energy systems for sustainable smart cities: Current developments, trends and future directions," Applied Energy, Elsevier, vol. 237(C), pages 581-597.
- Amina Ladhari & Heni Boubaker, 2024. "Deep Learning Models for Bitcoin Prediction Using Hybrid Approaches with Gradient-Specific Optimization," Forecasting, MDPI, vol. 6(2), pages 1-17, April.
- Pei-Chen Tsai & Tsung-Hua Lee & Kun-Chi Kuo & Fang-Yi Su & Tsung-Lu Michael Lee & Eliana Marostica & Tomotaka Ugai & Melissa Zhao & Mai Chan Lau & Juha P. Väyrynen & Marios Giannakis & Yasutoshi Takas, 2023. "Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
- Kristof Lommers & Ouns El Harzli & Jack Kim, 2021. "Confronting Machine Learning With Financial Research," Papers 2103.00366, arXiv.org, revised Mar 2021.
More about this item
Keywords
ultrasound image texture analysis; breast cancer prediction; explainable machine learning; ensemble classification; decision tree classification;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jforec:v:4:y:2022:i:1:p:15-274:d:748368. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.