Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,a...Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.展开更多
1.Introduction The synthesis of bulk nanostructured multiphase(NM)mate-rials with extreme properties such as high hardness and strength is one of the most interesting research topics in materials science and engineeri...1.Introduction The synthesis of bulk nanostructured multiphase(NM)mate-rials with extreme properties such as high hardness and strength is one of the most interesting research topics in materials science and engineering[1].At present,NM alloys can be produced by several synthesis methods,including sintering of nanocomposites[2,3],physical or chemical vapour deposition(PVD or CVD)[4],crystallization of metallic glasses[5],and severe plastic deforma-tion(SPD)[6-8].However,industry applications of bulk NM alloys produced by these methods are significantly restricted by their ge-ometrical and size limitations.Thus,the fabrication of large-scale NM alloys remains challenging.展开更多
基金supported by the National Natural Science Foundation of China(82302757)Shenzhen Science and Technology Program(JCY20240813145204006,SGDX20201103095600002,JCYJ20220818103417037,KJZD20230923115200002)+1 种基金Shenzhen Key Laboratory of Digital Surgical Printing Project(ZDSYS201707311542415)Shenzhen Development and Reform Program(XMHT20220106001).
文摘Osteoarthritis(OA)is a degenerative joint disease with significant clinical and societal impact.Traditional diagnostic methods,including subjective clinical assessments and imaging techniques such as X-rays and MRIs,are often limited in their ability to detect early-stage OA or capture subtle joint changes.These limitations result in delayed diagnoses and inconsistent outcomes.Additionally,the analysis of omics data is challenged by the complexity and high dimensionality of biological datasets,making it difficult to identify key molecular mechanisms and biomarkers.Recent advancements in artificial intelligence(AI)offer transformative potential to address these challenges.This review systematically explores the integration of AI into OA research,focusing on applications such as AI-driven early screening and risk prediction from electronic health records(EHR),automated grading and morphological analysis of imaging data,and biomarker discovery through multi-omics integration.By consolidating progress across clinical,imaging,and omics domains,this review provides a comprehensive perspective on how AI is reshaping OA research.The findings have the potential to drive innovations in personalized medicine and targeted interventions,addressing longstanding challenges in OA diagnosis and management.
基金funding from the Australian Research Council(ARC Discovery Project,Nos.DP200101408 and DP230100183).
文摘1.Introduction The synthesis of bulk nanostructured multiphase(NM)mate-rials with extreme properties such as high hardness and strength is one of the most interesting research topics in materials science and engineering[1].At present,NM alloys can be produced by several synthesis methods,including sintering of nanocomposites[2,3],physical or chemical vapour deposition(PVD or CVD)[4],crystallization of metallic glasses[5],and severe plastic deforma-tion(SPD)[6-8].However,industry applications of bulk NM alloys produced by these methods are significantly restricted by their ge-ometrical and size limitations.Thus,the fabrication of large-scale NM alloys remains challenging.
