传统医学、补充医学和综合医学与人工智能:医疗保健领域的新机遇

IF 2.8 4区 医学 Q2 INTEGRATIVE & COMPLEMENTARY MEDICINE
Jeremy Y. Ng , Holger Cramer , Myeong Soo Lee , David Moher
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引用次数: 0

摘要

传统医学、补充医学和综合医学(TCIM)与人工智能(AI)的融合是医疗保健领域前景广阔的前沿领域。传统医学、补充医学和综合医学是一种以病人为中心的方法,它将传统医学与补充疗法相结合,强调整体健康。人工智能可以通过数据驱动决策和个性化治疗方案彻底改变医疗保健。本文探讨了人工智能技术如何与 TCIM 相辅相成、相得益彰,并与这两个领域的研究人员在改善患者预后、提高护理质量和促进整体健康方面的共同目标保持一致。TCIM 与人工智能的融合带来了令人兴奋的机遇,同时也带来了值得注意的挑战。人工智能可以通过协助早期疾病检测、提供个性化治疗方案、预测健康趋势和提高患者参与度来增强 TCIM。人工智能与 TCIM 的交叉点面临的挑战包括数据隐私与安全、监管的复杂性、在患者与医疗服务提供者的关系中保持人情味,以及减少人工智能算法中的偏见。患者的信任、知情同意和法律责任都是必须考虑的因素。人工智能增强 TCIM 的未来发展方向包括先进的个性化医疗、了解草药疗法的疗效以及研究患者与医疗服务提供者之间的互动。在人工智能驱动的TCIM医疗保健中,有关减少偏见、患者接受度和信任度的研究至关重要。在这篇文章中,我们概述了 TCIM 与人工智能的融合在加强医疗服务、个性化治疗计划、预防性护理和患者参与方面的巨大前景。然而,应对挑战并促进人工智能专家、TCIM 从业人员和政策制定者之间的合作,对于充分发挥这种融合的潜力至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traditional, complementary, and integrative medicine and artificial intelligence: Novel opportunities in healthcare

The convergence of traditional, complementary, and integrative medicine (TCIM) with artificial intelligence (AI) is a promising frontier in healthcare. TCIM is a patient-centric approach that combines conventional medicine with complementary therapies, emphasizing holistic well-being. AI can revolutionize healthcare through data-driven decision-making and personalized treatment plans. This article explores how AI technologies can complement and enhance TCIM, aligning with the shared objectives of researchers from both fields in improving patient outcomes, enhancing care quality, and promoting holistic wellness. This integration of TCIM and AI introduces exciting opportunities but also noteworthy challenges. AI may augment TCIM by assisting in early disease detection, providing personalized treatment plans, predicting health trends, and enhancing patient engagement. Challenges at the intersection of AI and TCIM include data privacy and security, regulatory complexities, maintaining the human touch in patient-provider relationships, and mitigating bias in AI algorithms. Patients' trust, informed consent, and legal accountability are all essential considerations. Future directions in AI-enhanced TCIM include advanced personalized medicine, understanding the efficacy of herbal remedies, and studying patient-provider interactions. Research on bias mitigation, patient acceptance, and trust in AI-driven TCIM healthcare is crucial. In this article, we outlined that the merging of TCIM and AI holds great promise in enhancing healthcare delivery, personalizing treatment plans, preventive care, and patient engagement. Addressing challenges and fostering collaboration between AI experts, TCIM practitioners, and policymakers, however, is vital to harnessing the full potential of this integration.

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来源期刊
Integrative Medicine Research
Integrative Medicine Research Medicine-Complementary and Alternative Medicine
CiteScore
6.50
自引率
2.90%
发文量
65
审稿时长
12 weeks
期刊介绍: Integrative Medicine Research (IMR) is a quarterly, peer-reviewed journal focused on scientific research for integrative medicine including traditional medicine (emphasis on acupuncture and herbal medicine), complementary and alternative medicine, and systems medicine. The journal includes papers on basic research, clinical research, methodology, theory, computational analysis and modelling, topical reviews, medical history, education and policy based on physiology, pathology, diagnosis and the systems approach in the field of integrative medicine.
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