Predicting leishmaniasis outbreaks in Brazil using machine learning models based on disease surveillance and meteorological data

Operations Research for Health Care · Published 2024-11-20 · DOI 10.1016/j.orhc.2024.100453 · Cited by 8 (Crossref)

Authors being retrieved — see the publisher record. https://doi.org/10.1016/j.orhc.2024.100453

Abstract

PubPorta does not have an abstract for this article yet.

Read the article at the publisher →

Publication details

Year

2024

Related articles

• Health outcome predictive modelling in intensive care units · Operations Research for Health Care · 2023 · Same journal
• Predicting emergency medical service call demand: A modern spatiotemporal machine learning approach · Operations Research for Health Care · 2021 · Same journal
• An optimization model for distribution of influenza vaccines through a green healthcare supply chain · Operations Research for Health Care · 2023 · Same journal
• Outpatient appointment systems: A new heuristic with patient classification · Operations Research for Health Care · 2024 · Same journal
• An optimization framework to determine an optimal local sharing variance for organ allocation · Operations Research for Health Care · 2019 · Same journal
• Maximum matchings in graphs for allocating kidney paired donation · Operations Research for Health Care · 2020 · Same journal
• Surgical scheduling to smooth demand for resources · Operations Research for Health Care · 2023 · Same journal
• Addressing artificial variability in patient flow · Operations Research for Health Care · 2021 · Same journal
• Hospital flood emergency management planning using Markov models and discrete-event simulation · Operations Research for Health Care · 2021 · Same journal
• Analyzing the relationship between physicians’ experience and surgery duration · Operations Research for Health Care · 2022 · Same journal

Metrics

Citations (Crossref)

8