Experimental Analysis on Breast Cancer Using Random Forest Classifier on Histopathological Images-Reference-Cited by-同舟云学术

Experimental Analysis on Breast Cancer Using Random Forest Classifier on Histopathological Images

Published:2023-10-18 Issue: Volume: Page:
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Container-title:2023 International Conference on Self Sustainable Artificial Intelligence Systems (ICSSAS)
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Author:

Ramkumar G.¹,Sajiv G.¹

Affiliation:

1. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Department of Electronics and Communication Engineering,Chennai,Tamil Nadu,India,602105

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10330805/10331621/10331666.pdf?arnumber=10331666

Reference10 articles.

1. 2-Stage Convolutional Neural Network for Breast Cancer Detection from Ultrasound Images

2. Early Detection of Breast Cancer with IoT: A Promising Solution

3. A Breast Cancer Recurrence Risk Predictor Using a Deep Learning Multi-omics Data Integration Framework

4. Breast Cancer Imaging using a 24 GHz Ultra-Wideband MIMO FMCW Radar: System Considerations and First Imaging Results

5. Early Identification of cervical cancer using K-Nearest Neighbor (KNN)

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