A Study to Evaluate Various Machine Learning Approaches for Breast Cancer Prediction and Detection-Reference-Cited by-同舟云学术

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A Study to Evaluate Various Machine Learning Approaches for Breast Cancer Prediction and Detection

Published:2023-12-07 Issue: Volume:20 Page:619-624
ISSN:
Container-title:2023 International Conference on Modeling, Simulation & Intelligent Computing (MoSICom)
language:
Short-container-title:

Author:

Khatri Radhika¹,Ahmed Sanober Sarfaraz¹,Sood Neeru²,Gupta Anubhav³

Affiliation:

1. Birla Institute of Technology and Science Pilani,Department of Computer Science,UAE

2. Birla Institute of Technology and Science Pilani,Department of Biotechnology,UAE

3. University of British Columbia,Department of Computer Science, Mathematics, Physics and Statistics,Kelowna

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10458705/10458718/10458789.pdf?arnumber=10458789

Reference36 articles.

1. ANALYSIS OF MAMMOGRAPHY CLASSIFICATION DEEP LEARNING AND MACHINE LEARNING APPROACHES;Singh;Neuro-Quantology,2022

2. Comparison of the performance of machine learning algorithms in breast cancer screening and detection: A protocol

3. Deep Learning and Machine Learning with Grid Search to Predict Later Occurrence of Breast Cancer Metastasis Using Clinical Data

4. Logistic Regression: A Brief Primer

5. AI-assisted Emergency Healthcare using Vehicular Network and Support Vector Machine

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