Enhancing Gene Mutation Prediction With Sparse Regularized Autoencoders in Lung Cancer Radiomics Analysis

Enhancing Gene Mutation Prediction With Sparse Regularized Autoencoders in Lung Cancer Radiomics Analysis

Non-small cell lung cancer (NSCLC) remains the major contributor to global deaths annually. A slow and long screening and diagnostic process may lower 5-year survival rates. In cancer precision medicine, radiomics and machine learning are emerging as paradigm shifts in complementing cancer experts....

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Bibliographic Details
Main Authors: Muhammad Asif Munir, Reehan Ali Shah, Munwar Ali, Asif Ali Laghari, Ahmad Almadhor, Thippa Reddy Gadekallu
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Autoencoders
data augmentation
EGFR mutation
NSCLC
radiomics
synthetic data generation
Online Access:https://ieeexplore.ieee.org/document/10816594/

Internet

https://ieeexplore.ieee.org/document/10816594/

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