ArticleDigital health
A hybrid forecasting technique for infection and death from the mpox virus.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 27 citations in OpenAlex.
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- Enhancing the forecast accuracy of the daily number of patients arrivals in emergency department by hybrid ARIMAX-ANN algorithm.PloS one · 2026Article
- Clinical Application of Machine Learning Models for Early-Stage Chronic Kidney Disease Detection.Diagnostics (Basel, Switzerland) · 2025Article
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- Forecasting cardiovascular disease mortality using artificial neural networks in Sindh, Pakistan.BMC public health · 2025Article
- Incidence of acute hemorrhagic conjunctivitis in Chongqing: a forecasting study based on mathematical models.Frontiers in public health · 2025Article
- Comparative effectiveness analysis of univariate time-series forecasting models for disease mortality rates in the global burden of disease database: a case study of global hypertensive heart disease among women of childbearing age.Frontiers in public health · 2025Article
- Global burden and forecast of infectious diseases attributable to drug use: evidence from GBD 2021.Frontiers in public health · 2025Article
- A comprehensive analysis of the artificial neural networks model for predicting monkeypox outbreaks.Heliyon · 2024Article
- Optimal features selection in the high dimensional data based on robust technique: Application to different health database.Heliyon · 2024Review
- Evaluating the forecasting performance of ensemble sub-epidemic frameworks and other time series models for the 2022-2023 mpox epidemic.Royal Society open science · 2024Article
- Harnessing Artificial Intelligence and Innovative Vaccines for Mpox Diagnosis and Control: A Comprehensive Narrative Review.Journal of primary care & community healthReview
- MRpoxNet: An enhanced deep learning approach for early detection of monkeypox using modified ResNet50.Digital healthArticle
Corrections and comments
- Erratum issued
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: The rising of new cases and death counts from the mpox virus (MPV) is alarming. In order to mitigate the impact of the MPV it is essential to have information of the virus's future position using more precise time series and stochastic models. In this present study, a hybrid forecasting system has been developed for new cases and death counts for MPV infection using the world daily cumulative confirmed and death series. Methods: The original cumulative series was decomposed into new two subseries, such as a trend component and a stochastic series using the Hodrick-Prescott filter. To assess the efficacy of the proposed models, a comparative analysis with several widely recognized benchmark models, including auto-regressive (AR) model, auto-regressive moving average (ARMA) model, non-parametric auto-regressive (NPAR) model and artificial neural network (ANN), was performed. Results: The introduction of two novel hybrid models, Conclusion: The new models developed can be implemented in forecasting other diseases in the future. To address the current situation effectively, governments and stakeholders must implement significant changes to ensure strict adherence to standard operating procedures (SOPs) by the public. Given the anticipated continuation of increasing trends in the coming days, these measures are essential for mitigating the impact of the outbreak.
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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.