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

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外文摘要：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 prognosis,demonstrating its potential to be a non-invasive auxiliary tool for personalized medicine.However,radiomics remains in a developmental phase as numerous technical challenges have yet to be solved,especially in feature engineering and statistical modeling.In this review,we introduce the current utility of radiomics by summarizing research on its application in the diagnosis,prognosis,and prediction of treatment responses in patients with cancer.We focus on machine learning approaches,for feature extraction and selection during feature engineering and for imbalanced datasets and multi-modality fusion during statistical modeling.Furthermore,we introduce the stability,reproducibility,and interpretability of features,and the generalizability and interpretability of models.Finally,we offer possible solutions to current challenges in radiomics research.

外文关键词：

Artificial intelligenceRadiomicsFeature extractionFeature selectionModelingInterpretabilityMultimodalitiesHead and neck cancer

作者：

Yuan-Peng Zhang、Xin-Yun Zhang、Yu-Ting Cheng、Bing Li、Xin-Zhi Teng、Jiang Zhang、Saikit Lam、Ta Zhou、Zong-Rui Ma、Jia-Bao Sheng、Victor C.W.Tam、Shara W.Y.Lee、Hong Ge、Jing Cai

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作者单位：

Department of Medical Informatics,Nantong University,Nantong 226001,Jiangsu,China

Department of Health Technology and Informatics,the Hong Kong Polytechnic University,Hong Kong 999077,China

The Hong Kong Polytechnic University Shenzhen Research Institute,Shenzhen 518000,Guangdong,China

Department of Radiation Oncology,the Affiliated Cancer Hospital of Zhengzhou University and Henan Cancer Hospital,Zhengzhou 450008,China

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基金：

National Natural Science Foundation of ChinaShenzhen Basic Research ProgramShenzhen-Hong Kong-Macau S&T Program(Category C)Mainland-Hong Kong Joint Funding Scheme(MHKJFS)Project of Strategic Importance FundProjects of RISA from the Hong Kong Polytechnic UniversityNatural Science Foundation of Jiangsu ProvinceProvincial and Ministry Coconstructed Project of Henan Province Medical Science and Technology ResearchProvincial and Ministry Coconstructed Project of Henan Province Medical Science and Technology ResearchHenan Province Key R&D and Promotion Project(Science and Technology Research)Natural Science Foundation of Henan ProvinceHenan Province Science and Technology Research

项目编号：

82072019JCYJ20210324130209023SGDX20201103095002019MHP/005/20P0035421P0043001BK20201441SBGJ202103038SBGJ202102056222102310015222300420575222102310322

出版年：

2024

DOI：

10.1186/s40779-023-00458-8

军事医学研究(英文)

CSTPCD

ISSN：2095-7467

年,卷(期)：2024.11(1)

参考文献量198