Yagi Mitsuru, Yamanouchi Kento, Fujita Naruhito, Funao Haruki, Ebata Shigeto
Department of Orthopaedic Surgery, School of Medicine, International University of Health and Welfare, Narita 286-8686, Japan.
Department of Orthopaedic Surgery, International University of Health and Welfare and Narita Hospital, Narita 286-8520, Japan.
J Clin Med. 2023 Jun 21;12(13):4188. doi: 10.3390/jcm12134188.
Artificial intelligence (AI) and machine learning (ML) are rapidly becoming integral components of modern healthcare, offering new avenues for diagnosis, treatment, and outcome prediction. This review explores their current applications and potential future in the field of spinal care. From enhancing imaging techniques to predicting patient outcomes, AI and ML are revolutionizing the way we approach spinal diseases. AI and ML have significantly improved spinal imaging by augmenting detection and classification capabilities, thereby boosting diagnostic accuracy. Predictive models have also been developed to guide treatment plans and foresee patient outcomes, driving a shift towards more personalized care. Looking towards the future, we envision AI and ML further ingraining themselves in spinal care with the development of algorithms capable of deciphering complex spinal pathologies to aid decision making. Despite the promise these technologies hold, their integration into clinical practice is not without challenges. Data quality, integration hurdles, data security, and ethical considerations are some of the key areas that need to be addressed for their successful and responsible implementation. In conclusion, AI and ML represent potent tools for transforming spinal care. Thoughtful and balanced integration of these technologies, guided by ethical considerations, can lead to significant advancements, ushering in an era of more personalized, effective, and efficient healthcare.
人工智能(AI)和机器学习(ML)正迅速成为现代医疗保健不可或缺的组成部分,为诊断、治疗和结果预测提供了新途径。本综述探讨了它们在脊柱护理领域的当前应用和未来潜力。从增强成像技术到预测患者结果,人工智能和机器学习正在彻底改变我们处理脊柱疾病的方式。人工智能和机器学习通过增强检测和分类能力,显著改善了脊柱成像,从而提高了诊断准确性。还开发了预测模型来指导治疗计划和预见患者结果,推动向更个性化护理的转变。展望未来,随着能够解读复杂脊柱病变以辅助决策的算法的发展,我们设想人工智能和机器学习将进一步融入脊柱护理。尽管这些技术前景广阔,但将它们整合到临床实践中并非没有挑战。数据质量、整合障碍、数据安全和伦理考量是其成功和负责任实施需要解决的一些关键领域。总之,人工智能和机器学习是改变脊柱护理的有力工具。在伦理考量的指导下,对这些技术进行深思熟虑且平衡的整合,可带来重大进步,迎来一个更个性化、有效和高效的医疗保健时代。