Nahid Neoaz and Mohammad Hasan Amin (2025) Leveraging Artificial Intelligence for Early Lung Cancer Detection Through Advanced Imaging Analysis. Global Journal of Computer Sciences and Artificial Intelligence, 1 (1). pp. 55-65. ISSN 3079-5753
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Abstract
Lung cancer is still the worldwide leading cause of cancer deaths. Current testing methods can find lung cancer early, but standard tools like X-rays and CT scans often miss the right diagnosis or take too long for results. AI technology is revolutionizing how medical imaging helps find, diagnose, and track lung cancer, according to studies. This study looks at how AI boosts lung cancer imaging analysis by looking closely at machine learning (ML) and deep learning (DL) techniques, especially convolutional neural networks (CNNs). AI does three important things in medical imaging: it avoids human mistakes while doing analysis and speeds up work along with keeping results as accurate as possible. It has big potential, but first we need to fix three key problems: making sure our data is accurate, understanding how our models work, and making sure everything is done ethically. This article gives a complete look at the latest AI-based technology for lung cancer imaging, discussing both the progress made and the problems that need to be dealt with before AI can help healthcare professionals.
| Item Type: | Article |
|---|---|
| Date Deposited: | 14 Oct 2026 05:16 |
| Last Modified: | 14 Oct 2026 05:16 |
| URI: | https://repository.globalsciencepress.com/id/eprint/554 |
