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Background <p>In recent years, artificial intelligence (AI) has emerged as a&#xa0;new tool in oncology that can support in the detection of (pre)neoplastic lesions and deciphering carcinogenesis. In particular, modern AI models open up new perspectives for the identification and characterization of early cancer, for molecular subtyping, and for automated hypothesis generation from large multimodal datasets.</p> Materials and methods <p>This narrative review is based on a&#xa0;selective literature search in PubMed on current developments in the use of AI for early cancer detection, carcinogenesis, and research. For this purpose, the terms “AI early cancer detection/screening,” “AI tumor biomarker,” “AI carcinogenesis,” and “AI hypothesis generation oncology” were used, with a&#xa0;particular focus on recent studies published between 2022 and 2025.</p> Results <p>The scoping assessment reveals a&#xa0;wide range of current and emerging AI approaches, for example for use in early cancer detection. In parallel, multimodal AI methods, serum marker-based tumor screening, and foundation models for histopathology and multi-omics datasets are being intensively studied. Advances in AI agents and hypothesis-generating AI are also being addressed.</p> Conclusion <p>Artificial intelligence is already improving routine cancer diagnostics and can broaden the range of methods available for prevention and early detection. AI systems can furthermore drive precision medicine when combined with clinical, pathological, and molecular genetic data. At the same time, limitations such as model generalizability and safety must be continuously addressed before widespread clinical implementation can be achieved.</p>

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Künstliche Intelligenz und Karzinogenese

  • 期刊论文

  • 发表日期：

    2026年1月14日

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  • Stefan Schulz,
  • Sebastian Foersch

摘要

Background

In recent years, artificial intelligence (AI) has emerged as a new tool in oncology that can support in the detection of (pre)neoplastic lesions and deciphering carcinogenesis. In particular, modern AI models open up new perspectives for the identification and characterization of early cancer, for molecular subtyping, and for automated hypothesis generation from large multimodal datasets.

Materials and methods

This narrative review is based on a selective literature search in PubMed on current developments in the use of AI for early cancer detection, carcinogenesis, and research. For this purpose, the terms “AI early cancer detection/screening,” “AI tumor biomarker,” “AI carcinogenesis,” and “AI hypothesis generation oncology” were used, with a particular focus on recent studies published between 2022 and 2025.

Results

The scoping assessment reveals a wide range of current and emerging AI approaches, for example for use in early cancer detection. In parallel, multimodal AI methods, serum marker-based tumor screening, and foundation models for histopathology and multi-omics datasets are being intensively studied. Advances in AI agents and hypothesis-generating AI are also being addressed.

Conclusion

Artificial intelligence is already improving routine cancer diagnostics and can broaden the range of methods available for prevention and early detection. AI systems can furthermore drive precision medicine when combined with clinical, pathological, and molecular genetic data. At the same time, limitations such as model generalizability and safety must be continuously addressed before widespread clinical implementation can be achieved.