ArticleIEEE access : practical innovations, open solutions2020
Study on Prediction Model of HIV Incidence Based on GRU Neural Network Optimized by MHPSO.
Article in IEEE access : practical innovations, open solutions, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- Medical Artificial Intelligence: Opportunities and Challenges In Infectious Disease Management.Current medicinal chemistry · 2026Review
- Study on Univariate Modeling and Prediction Methods Using Monthly HIV Incidence and Mortality Cases in China.HIV/AIDS (Auckland, N.Z.) · 2024Article
- Article
- Application of artificial intelligence and machine learning for HIV prevention interventions.The lancet. HIV · 2022Review
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Acquired Immune Deficiency Syndrome (AIDS) is still one of the most life-threatening diseases in the world. Moreover, new infections are still potentially increasing. This difficult problem must be solved. Early warning is the most effective way to solve this problem. Here, we aim to determine the best performing model to track the epidemic of AIDS, which will provide a methodological basis for testing the time characteristics of the disease. From January 2004 to January 2018, we built four computing methods based on AIDS dataset: BPNN model, RNN model, LSTM model and MHPSO-GRU model. Compare the final estimated performance to determine the preferred method. Result. Considering the root mean square error (RMSE), mean absolute error (MAE), mean error rate (MER) and mean absolute percentage error (MAPE) in the simulation and prediction subsets, the MHPSO-GRU model is determined as the best performance technology. Estimates for the period from May 2018 to December 2020 suggest that the event appears to continue to increase and remain high.
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