Thrombosis and Hemostasis Labs, Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, United States of America.
Computational Pathology and AI Center of Excellence, University of Pittsburgh Medical Center, Pittsburgh, PA, United States of America.
Thromb Res. 2024 Oct;242:109121. doi: 10.1016/j.thromres.2024.109121. Epub 2024 Aug 23.
In this review, we embark on a comprehensive exploration of venous thromboembolism (VTE) in the context of medical history and its current practice within medicine. We delve into the landscape of artificial intelligence (AI), exploring its present utility and envisioning its transformative roles within VTE management, from prevention to screening and beyond. Central to our discourse is a forward-looking perspective on the integration of AI within VTE in medicine, advocating for rigorous study design, robust validation processes, and meticulous statistical analysis to gauge the efficacy of AI applications. We further illuminate the potential of large language models and generative AI in revolutionizing VTE care, while acknowledging their inherent limitations and proposing innovative solutions to overcome challenges related to data availability and integrity, including the strategic use of synthetic data. The critical importance of navigating ethical, legal, and privacy concerns associated with AI is underscored, alongside the imperative for comprehensive governance and policy frameworks to regulate its deployment in VTE treatment. We conclude on a note of cautious optimism, where we highlight the significance of proactively addressing the myriad challenges that accompany the advent of AI in healthcare. Through diligent design, stringent validation, extensive education, and prudent regulation, we can harness AI's potential to significantly enhance our understanding and management of VTE. As we stand on the cusp of a new era, our commitment to these principles will be instrumental in ensuring that the promise of AI is fully realized within the realm of VTE care.
在这篇综述中,我们全面探讨了静脉血栓栓塞症(VTE)在医学史上的地位及其当前的医学实践。我们深入研究了人工智能(AI)的现状,探讨了其在 VTE 管理中的应用,包括预防、筛查以及更广泛的领域。我们的讨论重点是前瞻性地看待 AI 在 VTE 医学中的整合,倡导严格的研究设计、稳健的验证流程和细致的统计分析,以评估 AI 应用的效果。我们进一步阐明了大型语言模型和生成式 AI 在改变 VTE 护理方面的潜力,同时认识到它们存在的固有局限性,并提出了创新的解决方案,以克服与数据可用性和完整性相关的挑战,包括战略性地使用合成数据。我们强调了与 AI 相关的伦理、法律和隐私问题的重要性,同时强调需要全面的治理和政策框架来规范其在 VTE 治疗中的应用。最后,我们以谨慎乐观的态度结束,强调积极应对 AI 在医疗保健领域带来的诸多挑战的重要性。通过精心设计、严格验证、广泛教育和审慎监管,我们可以利用 AI 的潜力,极大地提高我们对 VTE 的理解和管理水平。在我们即将进入一个新时代之际,我们致力于这些原则,将有助于确保 AI 的承诺在 VTE 护理领域得到充分实现。