A hybridized channel selection approach with deep convolutional neural network for effective ovarian cancer prediction in periodic acid‐Schiff‐stained images-Reference-Cited by-同舟云学术

A hybridized channel selection approach with deep convolutional neural network for effective ovarian cancer prediction in periodic acid‐Schiff‐stained images

Published:2022-12-13 Issue:5 Volume:35 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency and Computation

Author:

Ramasamy Sathya¹^ORCID,Kaliyaperumal Vaidehi²

Affiliation:

1. Department of IT Kongunadu College of Engineering and Technology Trichy Tamil Nadu India

2. Department of Artificial Intelligence and Data Science Stanley College of Engineering and Technology for Women Hyderabad Telangana India

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.7568

Reference33 articles.

1. Mechanical Modulation of Ovarian Cancer Tumor Nodules Under Flow

2. Graph theoretical way of understanding protein-protein interaction in ovarian cancer

3. European cancer mortality predictions for the year 2022 with focus on ovarian cancer

4. Deciphering serous ovarian carcinoma histopathology and platinum response by convolutional neural networks

5. Ovarian cancer detection using optical coherence tomography and convolutional neural networks

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