利用人工智能和数字健康应用推进肌肉骨骼护理:商业解决方案综述。

IF 1.6 4区 医学 Q3 ORTHOPEDICS
Johannes Pawelczyk, Moritz Kraus, Sebastian Voigtlaender, Sebastian Siebenlist, Marco-Christopher Rupp
{"title":"利用人工智能和数字健康应用推进肌肉骨骼护理:商业解决方案综述。","authors":"Johannes Pawelczyk, Moritz Kraus, Sebastian Voigtlaender, Sebastian Siebenlist, Marco-Christopher Rupp","doi":"10.1177/15563316251341321","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workflow optimization, and administrative burden reduction. AI-enabled triage systems enhance patient flow efficiency, while automated scheduling, symptom checkers, and AI-powered virtual assistants streamline pre-visit interactions. In MSK radiographic diagnostics, AI augments imaging interpretation, enabling automated fracture detection, opportunistic screening, and quantitative imaging, improving diagnostic accuracy and standardization. Preoperative planning solutions facilitate implant templating, surgical navigation, and patient-specific instrumentation, reducing variability and enhancing surgical precision. Concurrently, digital scribes and AI-driven documentation tools alleviate administrative overhead, mitigating clinician burnout and enabling refocused patient engagement. Predictive analytics optimize treatment pathways by leveraging multimodal patient data for risk stratification and personalized decision support. However, algorithmic bias, model generalizability, regulatory hurdles, and legal ambiguities present substantial implementation barriers, necessitating rigorous validation, adaptive governance, and seamless clinical integration. The U.S. and EU regulatory landscapes diverge in their approaches to AI oversight, with the former favoring expedited market access and the latter imposing stringent compliance mandates under the EU AI Act. AI's integration into MSK care demands robust validation frameworks, standardized interoperability protocols, and dynamic regulatory pathways balancing safety and innovation. Emerging generalist foundation models, open-source large language models (LLMs), and specialized AI-driven medical applications herald a paradigm shift toward precision MSK care. These innovations will require prospective clinical validation to ensure patient benefit and mitigate risk. Addressing ethical considerations, ensuring equitable access, and fostering interdisciplinary collaboration remain paramount in translating AI's potential into tangible improvements in MSK healthcare delivery.</p>","PeriodicalId":35357,"journal":{"name":"Hss Journal","volume":" ","pages":"15563316251341321"},"PeriodicalIF":1.6000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12126469/pdf/","citationCount":"0","resultStr":"{\"title\":\"Advancing Musculoskeletal Care Using AI and Digital Health Applications: A Review of Commercial Solutions.\",\"authors\":\"Johannes Pawelczyk, Moritz Kraus, Sebastian Voigtlaender, Sebastian Siebenlist, Marco-Christopher Rupp\",\"doi\":\"10.1177/15563316251341321\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workflow optimization, and administrative burden reduction. AI-enabled triage systems enhance patient flow efficiency, while automated scheduling, symptom checkers, and AI-powered virtual assistants streamline pre-visit interactions. In MSK radiographic diagnostics, AI augments imaging interpretation, enabling automated fracture detection, opportunistic screening, and quantitative imaging, improving diagnostic accuracy and standardization. Preoperative planning solutions facilitate implant templating, surgical navigation, and patient-specific instrumentation, reducing variability and enhancing surgical precision. Concurrently, digital scribes and AI-driven documentation tools alleviate administrative overhead, mitigating clinician burnout and enabling refocused patient engagement. Predictive analytics optimize treatment pathways by leveraging multimodal patient data for risk stratification and personalized decision support. However, algorithmic bias, model generalizability, regulatory hurdles, and legal ambiguities present substantial implementation barriers, necessitating rigorous validation, adaptive governance, and seamless clinical integration. The U.S. and EU regulatory landscapes diverge in their approaches to AI oversight, with the former favoring expedited market access and the latter imposing stringent compliance mandates under the EU AI Act. AI's integration into MSK care demands robust validation frameworks, standardized interoperability protocols, and dynamic regulatory pathways balancing safety and innovation. Emerging generalist foundation models, open-source large language models (LLMs), and specialized AI-driven medical applications herald a paradigm shift toward precision MSK care. These innovations will require prospective clinical validation to ensure patient benefit and mitigate risk. Addressing ethical considerations, ensuring equitable access, and fostering interdisciplinary collaboration remain paramount in translating AI's potential into tangible improvements in MSK healthcare delivery.</p>\",\"PeriodicalId\":35357,\"journal\":{\"name\":\"Hss Journal\",\"volume\":\" \",\"pages\":\"15563316251341321\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2025-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12126469/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hss Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/15563316251341321\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ORTHOPEDICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hss Journal","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/15563316251341321","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ORTHOPEDICS","Score":null,"Total":0}
引用次数: 0

摘要

人工智能(AI)和数字健康(DH)解决方案正在从诊断、治疗计划、工作流程优化和行政负担减轻等方面重塑肌肉骨骼(MSK)护理。支持人工智能的分诊系统提高了患者流程效率,而自动调度、症状检查器和人工智能驱动的虚拟助手简化了就诊前的互动。在MSK放射诊断中,人工智能增强了成像解释,实现了自动骨折检测、机会性筛查和定量成像,提高了诊断的准确性和标准化。术前计划解决方案有助于植入物模板、手术导航和患者特定的器械,减少可变性并提高手术精度。同时,数字抄写员和人工智能驱动的文档工具减轻了管理开销,减轻了临床医生的倦怠,并使患者重新关注。预测分析通过利用多模式患者数据进行风险分层和个性化决策支持来优化治疗途径。然而,算法偏差、模型可泛化性、监管障碍和法律模糊性构成了实质性的实施障碍,需要严格的验证、适应性治理和无缝的临床整合。美国和欧盟的监管格局在人工智能监管方面存在分歧,前者倾向于加快市场准入,后者则根据《欧盟人工智能法案》(EU AI Act)实施严格的合规要求。将人工智能集成到MSK护理中需要强大的验证框架、标准化的互操作性协议以及平衡安全和创新的动态监管途径。新兴的多面手基础模型、开源大型语言模型(llm)和专门的人工智能驱动的医疗应用预示着向精确MSK护理的范式转变。这些创新将需要前瞻性临床验证,以确保患者受益并降低风险。在将人工智能的潜力转化为MSK医疗保健服务的切实改进方面,解决伦理问题、确保公平获取和促进跨学科合作仍然至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancing Musculoskeletal Care Using AI and Digital Health Applications: A Review of Commercial Solutions.

Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workflow optimization, and administrative burden reduction. AI-enabled triage systems enhance patient flow efficiency, while automated scheduling, symptom checkers, and AI-powered virtual assistants streamline pre-visit interactions. In MSK radiographic diagnostics, AI augments imaging interpretation, enabling automated fracture detection, opportunistic screening, and quantitative imaging, improving diagnostic accuracy and standardization. Preoperative planning solutions facilitate implant templating, surgical navigation, and patient-specific instrumentation, reducing variability and enhancing surgical precision. Concurrently, digital scribes and AI-driven documentation tools alleviate administrative overhead, mitigating clinician burnout and enabling refocused patient engagement. Predictive analytics optimize treatment pathways by leveraging multimodal patient data for risk stratification and personalized decision support. However, algorithmic bias, model generalizability, regulatory hurdles, and legal ambiguities present substantial implementation barriers, necessitating rigorous validation, adaptive governance, and seamless clinical integration. The U.S. and EU regulatory landscapes diverge in their approaches to AI oversight, with the former favoring expedited market access and the latter imposing stringent compliance mandates under the EU AI Act. AI's integration into MSK care demands robust validation frameworks, standardized interoperability protocols, and dynamic regulatory pathways balancing safety and innovation. Emerging generalist foundation models, open-source large language models (LLMs), and specialized AI-driven medical applications herald a paradigm shift toward precision MSK care. These innovations will require prospective clinical validation to ensure patient benefit and mitigate risk. Addressing ethical considerations, ensuring equitable access, and fostering interdisciplinary collaboration remain paramount in translating AI's potential into tangible improvements in MSK healthcare delivery.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Hss Journal
Hss Journal Medicine-Surgery
CiteScore
3.90
自引率
0.00%
发文量
42
期刊介绍: The HSS Journal is the Musculoskeletal Journal of Hospital for Special Surgery. The aim of the HSS Journal is to promote cutting edge research, clinical pathways, and state-of-the-art techniques that inform and facilitate the continuing education of the orthopaedic and musculoskeletal communities. HSS Journal publishes articles that offer contributions to the advancement of the knowledge of musculoskeletal diseases and encourages submission of manuscripts from all musculoskeletal disciplines.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信