Rudroff Thorsten, Rainio Oona, Klén Riku
Turku PET Centre, University of Turku, Turku University Hospital, 20520 Turku, Finland.
Brain Sci. 2024 Aug 19;14(8):831. doi: 10.3390/brainsci14080831.
Long COVID (Coronavirus disease), affecting millions globally, presents unprecedented challenges to healthcare systems due to its complex, multifaceted nature and the lack of effective treatments. This perspective review explores the potential of artificial intelligence (AI)-guided transcranial direct current stimulation (tDCS) as an innovative approach to address the urgent need for effective Long COVID management. The authors examine how AI could optimize tDCS protocols, enhance clinical trial design, and facilitate personalized treatment for the heterogeneous manifestations of Long COVID. Key areas discussed include AI-driven personalization of tDCS parameters based on individual patient characteristics and real-time symptom fluctuations, the use of machine learning for patient stratification, and the development of more sensitive outcome measures in clinical trials. This perspective addresses ethical considerations surrounding data privacy, algorithmic bias, and equitable access to AI-enhanced treatments. It also explores challenges and opportunities for implementing AI-guided tDCS across diverse healthcare settings globally. Future research directions are outlined, including the need for large-scale validation studies and investigations of long-term efficacy and safety. The authors argue that while AI-guided tDCS shows promise for addressing the complex nature of Long COVID, significant technical, ethical, and practical challenges remain. They emphasize the importance of interdisciplinary collaboration, patient-centered approaches, and a commitment to global health equity in realizing the potential of this technology. This perspective article provides a roadmap for researchers, clinicians, and policymakers involved in developing and implementing AI-guided neuromodulation therapies for Long COVID and potentially other neurological and psychiatric conditions.
长期新冠(冠状病毒病)影响着全球数百万人,由于其复杂、多方面的性质以及缺乏有效治疗方法,给医疗系统带来了前所未有的挑战。这篇观点性综述探讨了人工智能(AI)引导的经颅直流电刺激(tDCS)作为一种创新方法的潜力,以满足有效管理长期新冠的迫切需求。作者研究了人工智能如何优化tDCS方案、加强临床试验设计,并为长期新冠的异质性表现促进个性化治疗。讨论的关键领域包括基于个体患者特征和实时症状波动的人工智能驱动的tDCS参数个性化、使用机器学习进行患者分层,以及在临床试验中开发更敏感的结局指标。这一观点涉及围绕数据隐私、算法偏差以及公平获得人工智能增强治疗的伦理考量。它还探讨了在全球不同医疗环境中实施人工智能引导的tDCS的挑战和机遇。概述了未来的研究方向,包括大规模验证研究的必要性以及对长期疗效和安全性的调查。作者认为,虽然人工智能引导的tDCS在应对长期新冠的复杂性质方面显示出前景,但重大的技术、伦理和实际挑战仍然存在。他们强调跨学科合作、以患者为中心的方法以及对全球卫生公平的承诺在实现这项技术潜力方面的重要性。这篇观点文章为参与开发和实施用于长期新冠以及可能其他神经和精神疾病的人工智能引导神经调节疗法的研究人员、临床医生和政策制定者提供了路线图。