Lung Cancer Diagnosis and Prediction from the Perspective of Artificial Intelligence

Wenting Li

2025

Abstract

Lung cancer remains one of the most prevalent and lethal malignancies worldwide, making early diagnosis and precise prediction critical for improving patient survival rates. Although conventional diagnostic approaches—such as imaging examinations and molecular testing—have achieved certain progress, they still exhibit limitations in early screening and complex case analysis. The integration of artificial intelligence (AI) has brought transformative advancements to lung cancer diagnosis and treatment. This paper first examines the pathological factors and clinical manifestations of lung cancer, followed by a discussion on the strengths and shortcomings of traditional diagnostic methods. Subsequently, it reviews AI-based diagnostic technologies for lung cancer, encompassing machine learning-based analytical approaches and deep learning-based automated feature extraction techniques, while comparing their performance and applicability in different scenarios. Finally, the study summarizes the current limitations of AI technologies—including strong data dependency, insufficient model interpretability, and other challenges—and explores future directions, such as few-shot learning, multimodal data fusion, and explainable AI (XAI). The objective of this research is to provide theoretical support and technical references for precision medicine in lung cancer, while promoting the standardized application of AI technologies in clinical practice.

Paper Citation

in Harvard Style

Li W. (2025). Lung Cancer Diagnosis and Prediction from the Perspective of Artificial Intelligence. In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-792-4, SciTePress, pages 203-208. DOI: 10.5220/0014325000004718

in Bibtex Style

@conference{emiti25,
author={Wenting Li},
title={Lung Cancer Diagnosis and Prediction from the Perspective of Artificial Intelligence},
booktitle={Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2025},
pages={203-208},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014325000004718},
isbn={978-989-758-792-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Lung Cancer Diagnosis and Prediction from the Perspective of Artificial Intelligence
SN - 978-989-758-792-4
AU - Li W.
PY - 2025
SP - 203
EP - 208
DO - 10.5220/0014325000004718
PB - SciTePress