Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images
Abstract Cancer is a global health concern because of a significant mortality rate and a wide range of affected organs. Early detection and accurate classification of cancer types are crucial for effective treatment. Imaging tests on different image modalities such as Histopathology images, provide...
Saved in:
Main Authors: | Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-02-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-025-86362-8 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
DESIGN ANALYSIS OF AN AUTOMATIC PHASE SELECTOR
by: ADEDOTUN O. OWOJORI, et al.
Published: (2022-01-01) -
Development of Hybrid Intrusion Detection System Leveraging Ensemble Stacked Feature Selectors and Learning Classifiers to Mitigate the DoS Attacks
by: P. Mamatha, et al.
Published: (2025-02-01) -
Histopathology : vol. 67, No. 6 /
Published: (2015) -
Adjunctive diagnostic tool for histopathological classification of congenital mesoblastic nephroma based in molecular genetic findings
by: Hiroshi Hamada, et al.
Published: (2025-02-01) -
Evaluation of the Chetomin effect on histopathological features in a murine acute spinal cord injury model
by: Carlos César Bravo-Reyna, et al.
Published: (2025-01-01)