AIMC Topic: Resource Allocation
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An interval type-2 fuzzy multi-criteria decision-making approach for patient bed allocation.
Scientific reports
Jul 1, 2025
Effective inpatient bed management is critical for optimizing healthcare resource utilization and ensuring high-quality patient care. The growing imbalance between bed capacity and patient demand underscores the need for robust, patient-centered prio...
Neural networks to model COVID-19 dynamics and allocate healthcare resources.
Scientific reports
May 2, 2025
This study presents a neural network-based framework for COVID-19 transmission prediction and healthcare resource optimization. The model achieves high prediction accuracy by integrating epidemiological, mobility, vaccination, and environmental data ...
Deep reinforcement learning can promote sustainable human behaviour in a common-pool resource problem.
Nature communications
Mar 22, 2025
A canonical social dilemma arises when resources are allocated to people, who can either reciprocate with interest or keep the proceeds. The right resource allocation mechanisms can encourage levels of reciprocation that sustain the commons. Here, in...
Ethical implications of AI-driven clinical decision support systems on healthcare resource allocation: a qualitative study of healthcare professionals' perspectives.
BMC medical ethics
Dec 21, 2024
BACKGROUND: Artificial intelligence-driven Clinical Decision Support Systems (AI-CDSS) are increasingly being integrated into healthcare for various purposes, including resource allocation. While these systems promise improved efficiency and decision...
Machine learning, healthcare resource allocation, and patient consent.
The New bioethics : a multidisciplinary journal of biotechnology and the body
Nov 15, 2024
The impact of machine learning in healthcare on patient informed consent is now the subject of significant inquiry in bioethics. However, the topic has predominantly been considered in the context of black box diagnostic or treatment recommendation a...
Joint computation offloading and resource allocation for end-edge collaboration in internet of vehicles via multi-agent reinforcement learning.
Neural networks : the official journal of the International Neural Network Society
Aug 8, 2024
Vehicular edge computing (VEC), a promising paradigm for the development of emerging intelligent transportation systems, can provide lower service latency for vehicular applications. However, it is still a challenge to fulfill the requirements of suc...
Differentially Private Client Selection and Resource Allocation in Federated Learning for Medical Applications Using Graph Neural Networks.
Sensors (Basel, Switzerland)
Aug 8, 2024
Federated learning (FL) has emerged as a pivotal paradigm for training machine learning models across decentralized devices while maintaining data privacy. In the healthcare domain, FL enables collaborative training among diverse medical devices and ...
Development and validation of a machine learning framework for improved resource allocation in the emergency department.
The American journal of emergency medicine
Jul 27, 2024
OBJECTIVE: The Emergency Severity Index (ESI) is the most commonly used system in over 70% of all U.S. emergency departments (ED) that uses predicted resource utilization as a means to triage [1], Mistriage, which includes both undertriage and overtr...
Managing low-acuity patients in an Emergency Department through simulation-based multiobjective optimization using a neural network metamodel.
Health care management science
Jun 10, 2024
This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on optimizing resource allocation in minor injuries units, which are the ED units that can treat low-acu...
Supporting equitable and responsible highway safety improvement funding allocation strategies - Why AI prediction biases matter.
Accident; analysis and prevention
Apr 17, 2024
The existing methodologies for allocating highway safety improvement funding closely rely on the utilization of crash prediction models. Specifically, these models produce predictions that estimate future crash hazard levels in different geographical...
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