1. Invited Review for 20th Anniversary Special Issue of PLRev "AI for Mechanomedicine".
- Author
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Xie, Ning, Tian, Jin, Li, Zedong, Shi, Nianyuan, Li, Bin, Cheng, Bo, Li, Ye, Li, Moxiao, and Xu, Feng
- Abstract
• AI enhances biomechanical model precision, improving prediction accuracy. • AI reveals novel mechanical signaling, advancing cellular response understanding. • AI boosts early disease detection using advanced mechanodiagnosis methods. • AI optimizes mechanotherapy with personalized strategies based on real-time data. • Challenges remain in data quality and ethical use of AI in clinical settings. Mechanomedicine is an interdisciplinary field that combines different areas including biomechanics, mechanobiology, and clinical applications like mechanodiagnosis and mechanotherapy. The emergence of artificial intelligence (AI) has revolutionized mechanomedicine, providing advanced tools to analyze the complex interactions between mechanics and biology. This review explores how AI impacts mechanomedicine across four key aspects, i.e. , biomechanics, mechanobiology, mechanodiagnosis, and mechanotherapy. AI improves the accuracy of biomechanical characterizations and models, deepens the understanding of cellular mechanotransduction pathways, and enables early disease detection through mechanodiagnosis. In addition, AI optimizes mechanotherapy that targets biomechanical features and mechanobiological markers by personalizing treatment strategies based on real-time patient data. Even with these advancements, challenges still exist, particularly in data quality and the ethical integration into AI in clinical practice. The integration of AI with mechanomedicine offers transformative potential, enabling more accurate diagnostics and personalized treatments, and discovering novel mechanobiological pathways. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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