Coordinated hospital patient scheduling

Decker, Keith; Li, Jinjiang

doi:10.1109/icmas.1998.699038

Cited by 95 publications

(57 citation statements)

References 3 publications

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“…Distributed patient scheduling with respect to appointments in different functional units within a hospital, [11], [3].…”

Section: Agent Technologiesmentioning

confidence: 99%

Software Design Framework for Healthcare Systems

KAmin¹,

Saini²,

Al-Gnabi³

2015

IJCA

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Healthcare is costing lot of money and resources all over the world in all countries; it consumes almost 30-40 percent of their budget in the healthcare industry. The only solution is to make this health care industry automated and online. In this paper we are proposing a software design framework for health care systems which will be based on agent technologies. The proposed system is based on Artificial Intelligence techniques that can support the user for selection and making choices. The proposed software framework suggested that Multi-Agent Systems (MAS) is the most suitable technique for designing such systems.MAS collaborate intelligently for solving this complex problem. Patients can be supported remotely using the proposed framework so that it can reduce the patient load on hospitals, the proposed software framework operate on real time framework. Computing can help in improving the communication process between follow-up doctors and nurses with patients by making appointments the process easier, according to patient preference with a reminder on necessary actions such as taking scheduled prescribed medicine, engaging in exercises, avoiding some kinds of food and harmful habits such as smoking before and after patient.

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“…Distributed patient scheduling with respect to appointments in different functional units within a hospital, [11], [3].…”

Section: Agent Technologiesmentioning

confidence: 99%

Software Design Framework for Healthcare Systems

KAmin¹,

Saini²,

Al-Gnabi³

2015

IJCA

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“…Especially, some of the related works focused on particular perspectives of the applications, such as vehicle dispatching and hospital patient scheduling [7]. However, in many circumstances, resource allocation and scheduling are closely related with each other as a dynamic system and will influence the operations of each other.…”

Section: Introductionmentioning

confidence: 99%

A General Framework of Resource Allocation Optimization and Dynamic Scheduling

Chang

Ichikawa²,

Deguchi

et al. 2017

SICE Journal of Control, Measurement, and System Integration

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: Resource allocation and scheduling under scarce resources and limited time are always critical and challenging tasks, not only because of the complex situation with diverse needs involved, but also of any unpredictable occurrence during the whole dynamic process. This work proposes an agent-based framework to integrate the resource allocation and scheduling under a set of limitations, which could respond to contingent changes as a dynamic system. We focus on the following research questions and formulate them as a constraint satisfaction problem: how many resources should be assigned and dispatched to which location, in which sequence and under what process scheduling with time, resource availability, and ability-matching limits. We first give the corresponding formal definition, and then combine real-coded genetic algorithm and dynamic scheduling of multi-functional resource assignment to tackle the above proposed research questions. In addition, we experiment the model with a small make-up case to suggest some preliminary scenarios. In future, this framework would be further applied to real life emergency situations with empirical data for training purposes and providing insight for relevant policy makers.

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“…Previous research in distributed scheduling has focused on a variety of domains including job-shop scheduling [19], airport scheduling [3] [14] and medical scheduling [10] [5]. One of the more influential ideas from previous research in distributed scheduling has been the communication of high-level information called texture measures [19].…”

Section: Distributed Schedulingmentioning

confidence: 99%

Bumping strategies for the multiagent agreement problem

Modi

Veloso

2005

Proceedings of the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems

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We introduce the Multiagent Agreement Problem (MAP) to represent a class of multiagent scheduling problems. MAP is based on the Distributed Constraint Reasoning (DCR) paradigm and requires agents to choose values for variables to satisfy not only their own constraints, but also equality constraints with other agents. The goal is to represent problems in which agents must agree on scheduling decisions, for example, to agree on the start time of a meeting. We investigate a challenging class of MAP -private, incremental MAP (piMAP) in which agents do incremental scheduling of activities and there exist privacy restrictions on information exchange. We investigate a range of strategies for piMAP, called "bumping" strategies. We empirically evaluate these strategies in the domain of calendar management where a personal assistant agent must schedule meetings on behalf of its human user. Our results show that bumping decisions based on scheduling difficulty models of other agents can significantly improve performance over simpler bumping strategies.

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Coordinated hospital patient scheduling

Cited by 95 publications

References 3 publications

Software Design Framework for Healthcare Systems

Software Design Framework for Healthcare Systems

A General Framework of Resource Allocation Optimization and Dynamic Scheduling

Bumping strategies for the multiagent agreement problem

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