Enhancing pancreatic cancer classification through dynamic weighted ensemble: a game theory approach-Reference-Cited by-同舟云学术

Enhancing pancreatic cancer classification through dynamic weighted ensemble: a game theory approach

Published:2023-11-20 Issue: Volume: Page:1-25
ISSN:1025-5842
Container-title:Computer Methods in Biomechanics and Biomedical Engineering
language:en
Short-container-title:Computer Methods in Biomechanics and Biomedical Engineering

Author:

S. Dhanasekaran¹,D. Silambarasan²,P. Vivek Karthick³,K. Sudhakar⁴

Affiliation:

1. Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

2. Department of Electronics and Communication Engineering, Sri Venkateswara College of Engineering, Tamil Nadu, India

3. Department of Electronics and Communication Engineering, Sona College of Technology, Salem, Tamil Nadu, India

4. Department of Electronics and Communication Engineering, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, India

Publisher

Informa UK Limited

Subject

Computer Science Applications,Human-Computer Interaction,Biomedical Engineering,General Medicine,Bioengineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10255842.2023.2281277

Reference44 articles.

1. Design of Optimal Deep Learning-Based Pancreatic Tumor and Nontumor Classification Model Using Computed Tomography Scans

2. Detection and diagnosis of pancreatic tumor using convolutional neural network and hybrid particle swarm optimization algorithm (CNN-HPSO) for image classification;Arulmozhi S;Annal Roman Soc Cell Biol,2021

3. Deep Transfer Learning for Pancreatic Cancer Detection

4. Artificial intelligence: a critical review of current applications in pancreatic imaging

5. Mixed-Sized Biomedical Image Segmentation Based on U-Net Architectures

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