reviewMilitary Medical ResearchMay 15, 2023DIAMOND OA

Artificial intelligence-driven radiomics study in cancer: the role of feature engineering and modeling

YZYuanpeng ZhangXZXinyun ZhangYCYu‐Ting ChengBLBing LiXTXin-Zhi Teng

Hong Kong Polytechnic University · Shenzhen Polytechnic University · +3 more institutions

PubMed
Indexed incrossrefdoajpubmed

Abstract

Modern medicine is reliant on various medical imaging technologies for non-invasively observing patients' anatomy. However, the interpretation of medical images can be highly subjective and dependent on the expertise of clinicians. Moreover, some potentially useful quantitative information in medical images, especially that which is not visible to the naked eye, is often ignored during clinical practice. In contrast, radiomics performs high-throughput feature extraction from medical images, which enables quantitative analysis of medical images and prediction of various clinical endpoints. Studies have reported that radiomics exhibits promising performance in diagnosis and predicting treatment responses and…

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183
total citations
FWCI
40.84
Percentile
100%
References
200
Citations per year

Authors

14

Topics & keywords

Topics
Keywords
  • Interpretability
  • Radiomics
  • Artificial intelligence
  • Feature selection
  • Generalizability theory
  • Machine learning
  • Feature (linguistics)
  • Computer science
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