Haick Hossam, Tang Ning
The Department of Chemical Engineering and the Russell Berrie Nanotechnology Institute, Technion - Israel Institute of Technology, Haifa 3200003, Israel.
ACS Nano. 2021 Mar 23;15(3):3557-3567. doi: 10.1021/acsnano.1c00085. Epub 2021 Feb 23.
Due to the limited ability of conventional methods and the limited perspective of human diagnostics, patients are often diagnosed incorrectly or at a late stage as their disease condition progresses. They may then undergo unnecessary treatments due to inaccurate diagnoses. In this Perspective, we offer a brief overview on the integration of nanotechnology-based medical sensors and artificial intelligence (AI) for advanced clinical decision support systems to help decision-makers and healthcare systems improve how they approach information, insights, and the surrounding contexts, as well as to promote the uptake of personalized medicine on an individualized basis. Relying on these milestones, wearable sensing devices could enable interactive and evolving clinical decisions that could be used for evidence-based analysis and recommendations as well as for personalized monitoring of disease progress and treatment. We present and discuss the ongoing challenges and future opportunities associated with AI-enabled medical sensors in clinical decisions.
由于传统方法能力有限且人类诊断视角受限,随着病情发展,患者常常被误诊或在疾病晚期才被诊断出来。由于诊断不准确,他们可能会接受不必要的治疗。在这篇观点文章中,我们简要概述了基于纳米技术的医学传感器与人工智能(AI)相结合用于先进临床决策支持系统的情况,以帮助决策者和医疗系统改进他们处理信息、见解及周围环境的方式,并促进个性化医疗在个体层面的应用。基于这些里程碑,可穿戴传感设备能够实现交互式且不断发展的临床决策,这些决策可用于循证分析和建议,以及对疾病进展和治疗的个性化监测。我们介绍并讨论了在临床决策中与人工智能驱动的医学传感器相关的当前挑战和未来机遇。