AIMC Topic: Health Care Rationing
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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...
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...
A Machine Learning Method for Allocating Scarce COVID-19 Monoclonal Antibodies.
JAMA health forum
Sep 6, 2024
IMPORTANCE: During the COVID-19 pandemic, the effective distribution of limited treatments became a crucial policy goal. Yet, limited research exists using electronic health record data and machine learning techniques, such as policy learning trees (...
SARS-CoV-2
Hospitalization
Aged
Retrospective Studies
Electronic Health Records
Female
Middle Aged
Severity of Illness Index
Adolescent
Antibodies, Viral
Young Adult
Adult
Male
Machine Learning
COVID-19
Emergency Use Authorization
Humans
Health Policy
United States Food and Drug Administration
Antibodies, Monoclonal
COVID-19 Drug Treatment
Random Forest
Health Care Rationing
[Prioritized appointment allocation in new patients, what is really decisive? : Comparative analysis of manual appointment allocation with automated and AI-assisted approaches].
Zeitschrift fur Rheumatologie
Aug 16, 2024
BACKGROUND: The timely allocation of appointments for new patients is a daily challenge in rheumatological practice, which can be supported by digital solutions. The question is to find the simplest and most effective possible method for prioritizati...
Validation of a Machine Learning Model to Predict Childhood Lead Poisoning.
JAMA network open
Sep 1, 2020
IMPORTANCE: Childhood lead poisoning causes irreversible neurobehavioral deficits, but current practice is secondary prevention.
Ensuring Fairness in Machine Learning to Advance Health Equity.
Annals of internal medicine
Dec 4, 2018
Machine learning is used increasingly in clinical care to improve diagnosis, treatment selection, and health system efficiency. Because machine-learning models learn from historically collected data, populations that have experienced human and struct...
An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach.
Health care management science
Aug 9, 2017
Given the perennial imbalance and chronic scarcity between the demand for and supply of available organs, organ allocation is one of the most critical decisions in the management of organ transplantation networks. Organ allocation systems undergo rap...
Improving Hospital-Wide Early Resource Allocation through Machine Learning.
Studies in health technology and informatics
Jan 1, 2015
The objective of this paper is to evaluate the extent to which early determination of diagnosis-related groups (DRGs) can be used for better allocation of scarce hospital resources. When elective patients seek admission, the true DRG, currently deter...
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