ArticleScientific reports2025
A gravity model for emergency departments.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Toward a new AI winter? How diffusion of technological innovation on networks leads to chaotic boom-bust cycles.Frontiers in artificial intelligence · 2025Article
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The issue of facility location is of significant importance in numerous systems, where the efficient utilisation of resources is of great importance. Gravity models, which are inspired by Newtonian physics, are commonly employed to address these problems and have a long tradition of being used in healthcare. The objective of this paper is to enhance the comprehension of patients' decision-making processes in emergency healthcare by introducing an extension to existing gravity models, which includes two novel factors influencing emergency department choice: hospital sizes and patients' severity. The newly formulated gravity rule, which integrates these factors, demonstrated an extremely high accuracy against real-world data in terms of overall hospital location and flows between cities and hospitals, respectively 98.77% and 98.02%.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.