Artificial intelligence‐enabled digital biomedical engineering

Abstract Artificial intelligence (AI) has emerged as a transformative force in biomedical engineering, catalyzing a shift toward data‐driven, intelligent research paradigms. With its advanced capabilities in computation, pattern recognition, and large‐scale data analysis, AI significantly enhances the efficiency, precision, and reproducibility of biomedical research. In particular, the convergence of AI with biomedical engineering has given rise to the emerging field of Digital Biomedical Engineering, which emphasizes the integration of AI technologies, big data analytics, and computational modeling to enable smart, predictive, and personalized solutions across life sciences. This review provides a comprehensive overview of the current landscape of AI applications in biomedical engineering, highlighting advances in medical image analysis, biosignal processing, biomaterials design, and drug development. It also emphasizes how AI improves diagnostic precision, accelerates material and drug discovery, and fosters personalized and predictive medicine. Additionally, it discusses the limitations and regulatory challenges of AI adoption, while outlining future directions to guide research innovation and clinical translation in the era of digital biomedicine.

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Publication Details

Journal
BMEMat
Published
2025-12-01
DOI
https://doi.org/10.1002/bmm2.70049
Primary Topic
Advanced Technologies in Various Fields
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial intelligence‐enabled digital biomedical engineering

Long Bai, Rui Luís Reis, Xiao Chen, Xuan Tang et al.
BMEMat
Advanced Technologies in Various Fields
article

Artificial intelligence‐enabled digital biomedical engineering

Long Bai, Rui Luís Reis, Xiao Chen, Xuan Tang, Xukun Lv, Peiran Song, Jiacan Su
article en

Abstract

Abstract Artificial intelligence (AI) has emerged as a transformative force in biomedical engineering, catalyzing a shift toward data‐driven, intelligent research paradigms. With its advanced capabilities in computation, pattern recognition, and large‐scale data analysis, AI significantly enhances the efficiency, precision, and reproducibility of biomedical research. In particular, the convergence of AI with biomedical engineering has given rise to the emerging field of Digital Biomedical Engineering, which emphasizes the integration of AI technologies, big data analytics, and computational modeling to enable smart, predictive, and personalized solutions across life sciences. This review provides a comprehensive overview of the current landscape of AI applications in biomedical engineering, highlighting advances in medical image analysis, biosignal processing, biomaterials design, and drug development. It also emphasizes how AI improves diagnostic precision, accelerates material and drug discovery, and fosters personalized and predictive medicine. Additionally, it discusses the limitations and regulatory challenges of AI adoption, while outlining future directions to guide research innovation and clinical translation in the era of digital biomedicine.

BMEMatVol. 3(4)
Shanghai University (CN), Wenzhou University (CN), Shanghai Jiao Tong University (CN), New York University Shanghai (CN), XinHua Hospital (CN), Shanghai Institutes for Biological Sciences (CN), Osaka Prefectural Government (JP), Regenerative Medicine Institute (MX)
China Association for Science and Technology, National Natural Science Foundation of China, China Postdoctoral Science Foundation
Openalex Percentile: Top 79%
Advanced Technologies in Various Fields
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