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February 17, 2026Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery

Lung Cancer in the New Era: Trends, Innovations, and Future Recommendations

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Authors

MAMohd Munazzer AnsariSKShailendra KumarMHMd Belal Bin Heyat

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Overview

This review explores AI innovations for lung cancer detection and treatment, suggesting solutions to overcome barriers.

Key Points

  • The aim is to assess how AI and modern techniques improve lung cancer detection, classification, and treatment.
  • Review of advancements in AI and ML for lung cancer detection and treatment
  • Analysis of deep learning techniques, particularly convolutional neural networks
  • Discussion on environmental risk factors and their integration into AI systems
  • Identification of barriers to clinical adoption of AI approaches
  • AI and DL methods outperform traditional techniques in analyzing lung cancer scans.
  • Tailored treatment plans based on genetic variations lead to better outcomes and fewer side effects.
  • AI can identify high-risk groups by integrating environmental factors like air pollution.

Cite This Study

Ansari et al. (2026) studied this question.

synapsesocial.com/papers/6994055d4e9c9e835dfd63f0https://doi.org/10.1002/widm.70061
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Artificial Intelligence in Lung Cancer Management: Innovations, Challenges, and Clinical Translation2026
  2. 2The Impact of Artificial Intelligence on Lung Cancer Diagnosis and Personalized Treatment2025 · 13 citations
  3. 3The Promising Role of Artificial Intelligence in Navigating Lung Cancer Prognosis2024 · 3 citations
  4. 4The Application of Machine Learning in the Diagnosis of Lung Cancer2025
  5. 5Lung Cancer Prediction with Machine Learning, Deep Learning and Hybrid Techniques: A Survey2026 · 2 citations