Improving hospital layout planning through clinical pathway mining

DOI10.1007/s10479-017-2485-4zbMath1462.62645OpenAlexW2604431738WikidataQ59529190 ScholiaQ59529190MaRDI QIDQ1639251

Ines Verena Arnolds, Daniel Gartner

Publication date: 12 June 2018

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-017-2485-4

zbMATH Keywords

machine learningclinical pathwayshealthcare operations managementsequential pattern mininghospital layout planningprobabilistic finite state automata (PFSA)

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Management decision making, including multiple objectives (90B50) Sequential statistical analysis (62L10)

Related Items (1)

Adaptive layout for operating theatre in hospitals: different mathematical models for optimal layouts

Uses Software

• PRMLT

Cites Work

• Unnamed Item
• Scheduling the hospital-wide flow of elective patients
• Simulation and estimation of extreme quantiles and extreme probabilities
• Inference for the generalization error
• Mining probabilistic automata: a statistical view of sequential pattern mining
• Links between probabilistic automata and hidden Markov models: probability distributions, learning models and induction algorithms
• A new linearization method for quadratic assignment problems
• Hospital Layout as a Quadratic Assignment Problem
• Probability Inequalities for Sums of Bounded Random Variables
• Hastings-Metropolis algorithm on Markov chains for small-probability estimation

This page was built for publication: Improving hospital layout planning through clinical pathway mining