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人工智能作为中风和癫痫临床决策的辅助工具。

Artificial Intelligence as A Complementary Tool for Clincal Decision-Making in Stroke and Epilepsy.

作者信息

Shah Smit P, Heiss John D

机构信息

Resident Physician, University of South Carolina School of Medicine, PRISMA Health Richland, Columbia, SC 29203, USA.

Senior Clinician and Neurosurgical Residency Director, Surgical Neurology Branch [SNB], Building 10, Room 3D20, 10 Center Drive, Bethesda, MD 20814, USA.

出版信息

Brain Sci. 2024 Feb 28;14(3):228. doi: 10.3390/brainsci14030228.

Abstract

Neurology is a quickly evolving specialty that requires clinicians to make precise and prompt diagnoses and clinical decisions based on the latest evidence-based medicine practices. In all Neurology subspecialties-Stroke and Epilepsy in particular-clinical decisions affecting patient outcomes depend on neurologists accurately assessing patient disability. Artificial intelligence [AI] can predict the expected neurological impairment from an AIS [Acute Ischemic Stroke], the possibility of ICH [IntraCranial Hemorrhage] expansion, and the clinical outcomes of comatose patients. This review article informs readers of artificial intelligence principles and methods. The article introduces the basic terminology of artificial intelligence before reviewing current and developing AI applications in neurology practice. AI holds promise as a tool to ease a neurologist's daily workflow and supply unique diagnostic insights by analyzing data simultaneously from several sources, including neurological history and examination, blood and CSF laboratory testing, CNS electrophysiologic evaluations, and CNS imaging studies. AI-based methods are poised to complement the other tools neurologists use to make prompt and precise decisions that lead to favorable patient outcomes.

摘要

神经病学是一个快速发展的专业领域,要求临床医生依据最新的循证医学实践做出准确且迅速的诊断和临床决策。在所有神经病学亚专业中,尤其是中风和癫痫领域,影响患者预后的临床决策取决于神经科医生对患者残疾情况的准确评估。人工智能(AI)可以预测急性缺血性卒中(AIS)可能导致的神经功能缺损、颅内出血(ICH)扩展的可能性以及昏迷患者的临床预后。这篇综述文章向读者介绍人工智能的原理和方法。在回顾当前及正在发展的神经病学实践中的人工智能应用之前,文章先介绍了人工智能的基本术语。人工智能有望成为一种工具,通过同时分析来自多个来源的数据,包括神经病史和检查、血液和脑脊液实验室检测、中枢神经系统电生理评估以及中枢神经系统影像学研究,来简化神经科医生的日常工作流程并提供独特的诊断见解。基于人工智能的方法有望补充神经科医生用于做出迅速且准确决策以实现患者良好预后的其他工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5fa/10968980/9566dd5cdb0a/brainsci-14-00228-g001.jpg

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