From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non‐Invasive Precision Medicine in Cancer Patients
Abstract: With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high‐throughput technologies with imaging phenotypes. However, with advancements in medical imaging, high‐throughput omics technologies, and artificial intelligence, both the concept and application of radiogenomics have significantly broadened. In this review, the history of radiogenomics is enumerated, related omics technologies, the five basic workflows and their applications across tumors, the role of AI in radiogenomics, the opportunities and challenges from tumor heterogeneity, and the applications of radiogenomics in tumor immune microenvironment. The application of radiogenomics in positron emission tomography and the role of radiogenomics in multi‐omics studies is also discussed. Finally, the challenges faced by clinical transformation, along with future trends in this field is discussed.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non‐Invasive Precision Medicine in Cancer Patients ; day:13 ; month:11 ; year:2024 ; extent:29
Advanced science ; (13.11.2024) (gesamt 29)
- Creator
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Guo, Yusheng
Li, Tianxiang
Gong, Bingxin
Hu, Yan
Wang, Sichen
Yang, Lian
Zheng, Chuansheng
- DOI
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10.1002/advs.202408069
- URN
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urn:nbn:de:101:1-2411131355233.776467309140
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:26 AM CEST
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Associated
- Guo, Yusheng
- Li, Tianxiang
- Gong, Bingxin
- Hu, Yan
- Wang, Sichen
- Yang, Lian
- Zheng, Chuansheng
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