Lung Cancer Classification using Convolutional Neural Networks Learning approach and Support Vector Machine Technique
DOI:
https://doi.org/10.48001/978-81-980647-5-2-8Keywords:
Lung cancer classification, Machine learning, CNN, Data preprocessingAbstract
Lung cancer is a major cause of cancer-related deaths globally, making early, accurate diagnosis crucial for improving patient outcomes. Traditional diagnostic methods like imaging and histological analysis are time-intensive and require expert interpretation. Machine learning (ML) has emerged as a powerful tool for lung cancer classification, enabling analysis of large datasets to uncover complex patterns. This chapter reviews ML techniques such as Support Vector Machines (SVM) and Convolutional Neural Networks (CNNs), highlighting their strengths, limitations, and the importance of data preprocessing, feature extraction, and model evaluation. It also explores advancements in deep learning, ensemble methods, and multimodal approaches to enhance clinical decision-making and personalize lung cancer treatment.
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