ArticlePLoS neglected tropical diseases2013
Transmission risks of schistosomiasis japonica: extraction from back-propagation artificial neural network and logistic regression model.
Article in PLoS neglected tropical diseases, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.
- Socioeconomic Inequalities in Neglected Tropical Diseases: A Systematic Review.PLoS neglected tropical diseases · 2016Pooled it
- Effect of Genetic Polymorphisms on the Pharmacokinetics of Deferasirox in Healthy Chinese Subjects and an Artificial Neural Networks Model for Pharmacokinetic Prediction.European journal of drug metabolism and pharmacokinetics · 2020Trial
- Field Testing Integrated Interventions for Schistosomiasis Elimination in the People's Republic of China: Outcomes of a Multifactorial Cluster-Randomized Controlled Trial.Frontiers in immunology · 2019Trial
- Economic Evaluation of Multi-Objective Schistosomiasis Control Through Systemic Causality: Theoretical Advances and Governance Implications.Tropical medicine and infectious disease · 2026Review
- Spatiotemporal distribution of schistosomiasis transmission risk in Jiangling County, Hubei Province, P.R. China.PLoS neglected tropical diseases · 2023Article
- Prediction of SMILE surgical cutting formula based on back propagation neural network.International journal of ophthalmology · 2023Article
- A stepwise strategy integrating metabolomics and pseudotargeted spectrum-effect relationship to elucidate the potential hepatotoxic components inFrontiers in pharmacology · 2022Article
- Association of Salt-Reduction Knowledge and Behaviors and Salt Intake in Chinese Population.Frontiers in public health · 2022Article
- Identification of the high-risk area for schistosomiasis transmission in China based on information value and machine learning: a newly data-driven modeling attempt.Infectious diseases of poverty · 2021Article
- Using Metabolic and Biochemical Indicators to Predict Diabetic Retinopathy by Back-Propagation Artificial Neural Network.Diabetes, metabolic syndrome and obesity : targets and therapy · 2021Article
- Assessment of knowledge, attitude and practices and the analysis of risk factors regarding schistosomiasis among fishermen and boatmen in the Dongting Lake Basin, the People's Republic of China.Parasites & vectors · 2020Article
- Discovery of Hepatotoxic Equivalent Combinatorial Markers from Dioscorea bulbifera tuber by Fingerprint-Toxicity Relationship Modeling.Scientific reports · 2018Article
- Correlations of Complete Blood Count with Alanine and Aspartate Transaminase in Chinese Subjects and Prediction Based on Back-Propagation Artificial Neural Network (BP-ANN).Medical science monitor : international medical journal of experimental and clinical research · 2017Article
- Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.Lipids in health and disease · 2017Article
- Prediction of liver injury using the BP-ANN model with metabolic parameters in overweight and obese Chinese subjects.International journal of clinical and experimental medicine · 2015Article
- Reduction patterns of acute schistosomiasis in the People's Republic of China.PLoS neglected tropical diseases · 2014Article
- Field comparison of circulating antibody assays versus circulating antigen assays for the detection of schistosomiasis japonica in endemic areas of China.Parasites & vectors · 2014Article
- A hybrid model for predicting the prevalence of schistosomiasis in humans of Qianjiang City, China.PloS one · 2014Article
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Authors and funding
11 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe transmission of schistosomiasis japonica in a local setting is still poorly understood in the lake regions of the People's Republic of China (P. R. China), and its transmission patterns are closely related to human, social and economic factors. METHODOLOGY/PRINCIPAL
findingsWe aimed to apply the integrated approach of artificial neural network (ANN) and logistic regression model in assessment of transmission risks of Schistosoma japonicum with epidemiological data collected from 2339 villagers from 1247 households in six villages of Jiangling County, P.R. China. By using the back-propagation (BP) of the ANN model, 16 factors out of 27 factors were screened, and the top five factors ranked by the absolute value of mean impact value (MIV) were mainly related to human behavior, i.e. integration of water contact history and infection history, family with past infection, history of water contact, infection history, and infection times. The top five factors screened by the logistic regression model were mainly related to the social economics, i.e. village level, economic conditions of family, age group, education level, and infection times. The risk of human infection with S. japonicum is higher in the population who are at age 15 or younger, or with lower education, or with the higher infection rate of the village, or with poor family, and in the population with more than one time to be infected. CONCLUSION/SIGNIFICANCE: Both BP artificial neural network and logistic regression model established in a small scale suggested that individual behavior and socioeconomic status are the most important risk factors in the transmission of schistosomiasis japonica. It was reviewed that the young population (≤15) in higher-risk areas was the main target to be intervened for the disease transmission control.
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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.