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首页> 外文期刊>Automatic Control, IEEE Transactions on >A Monte Carlo Optimization and Dynamic Programming Approach for Managing MRI Examinations of Stroke Patients
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A Monte Carlo Optimization and Dynamic Programming Approach for Managing MRI Examinations of Stroke Patients

机译：用于中风患者MRI检查的Monte Carlo优化和动态规划方法

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摘要

Quick diagnosis is critical to stroke patients, but it relies on expensive and heavily used imaging equipment. This results in long waiting times with potential threats to the patient's life. It is important for neurovascular departments treating stroke patients to reduce waiting times for diagnosis. This paper proposes a reservation process of magnetic resonance imaging (MRI) examinations for stroke patients. The neurovascular department reserves a certain number of appropriately distributed contracted time slots (CTS) to ensure quick diagnosis of stroke patients. Additional MRI time slots can also be reserved by regular reservations (RTS). The problem consists in determining the contract and the control policy to assign patients to either CTS or RTS in order to reach the best compromise between the waiting times and unused CTS. Structural properties of the optimal control policy are proved by an average-cost Markov decision process (MDP) approach. The contract is determined by combining a Monte Carlo approximation approach and local search. Extensive numerical experiments are performed to show the efficiency of the proposed approach and to investigate the impact of different parameters.
机译：快速诊断对中风患者至关重要，但它依赖于昂贵且使用频繁的成像设备。这会导致漫长的等待时间，对患者的生命造成潜在威胁。对于中风患者的神经血管部门来说，减少等待诊断的时间很重要。本文提出了中风患者磁共振成像（MRI）检查的预约过程。神经血管部门保留一定数量的适当分布的合同规定的时隙（CTS），以确保快速诊断中风患者。也可以通过常规保留（RTS）保留其他MRI时隙。问题在于确定合同和控制策略以将患者分配到CTS或RTS，以便在等待时间和未使用的CTS之间达成最佳折衷。最优控制策略的结构特性通过平均成本马尔可夫决策过程（MDP）方法得到证明。通过组合蒙特卡罗近似方法和局部搜索来确定合同。进行了广泛的数值实验，以证明所提出方法的效率并研究不同参数的影响。

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