AIMC Topic: Brucellosis

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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.

Frontiers in cellular and infection microbiology Jan 13, 2025
INTRODUCTION: This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis.
Male Biomarkers Humans Middle Aged Female Computational Biology Machine Learning Adult Brucellosis Algorithms Proteomics Enzyme-Linked Immunosorbent Assay Proteome
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Spatial prediction of human brucellosis susceptibility using an explainable optimized adaptive neuro fuzzy inference system.

Acta tropica Nov 30, 2024
Brucellosis, a zoonotic disease caused by Brucella bacteria, poses significant risks to human, livestock, and wildlife health, alongside economic losses from livestock morbidity and mortality. This study improves Human Brucellosis Susceptibility Mapp...
Fuzzy Logic Iran Spatial Analysis Disease Susceptibility Algorithms Animals Brucellosis Humans Brucella
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Differentiation of tuberculous and brucellar spondylitis using conventional MRI-based deep learning algorithms.

European journal of radiology Jul 27, 2024
PURPOSE: To investigate the feasibility of deep learning (DL) based on conventional MRI to differentiate tuberculous spondylitis (TS) from brucellar spondylitis (BS).
Humans Algorithms Female Aged Brucellosis Magnetic Resonance Imaging Diagnosis, Differential Spondylitis Feasibility Studies Tuberculosis, Spinal Male Middle Aged Deep Learning Young Adult Adult Sensitivity and Specificity
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Predictive analysis of the number of human brucellosis cases in Xinjiang, China.

Scientific reports Jun 1, 2021
Brucellosis is one of the major public health problems in China, and human brucellosis represents a serious public health concern in Xinjiang and requires a prediction analysis to help making early planning and putting forward science preventive and ...
Female Male China Incidence Neural Networks, Computer Forecasting Retrospective Studies Brucellosis Models, Biological Seasons Humans
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Spatial prediction of human brucellosis (HB) using a GIS-based adaptive neuro-fuzzy inference system (ANFIS).

Acta tropica May 9, 2021
OBJECTIVE: This study pursues three main objectives: 1) exploring the spatial distribution patterns of human brucellosis (HB); 2) identifying parameters affecting the disease spread; and 3) modeling and predicting the spatial distribution of HB cases...
Fuzzy Logic Cluster Analysis Models, Statistical Climate Spatial Analysis Linear Models Geographic Information Systems Incidence Brucellosis Humans Neural Networks, Computer Animals
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Research on the predictive effect of a combined model of ARIMA and neural networks on human brucellosis in Shanxi Province, China: a time series predictive analysis.

BMC infectious diseases Mar 19, 2021
BACKGROUND: Brucellosis is a major public health problem that seriously affects developing countries and could cause significant economic losses to the livestock industry and great harm to human health. Reasonable prediction of the incidence is of gr...
Neural Networks, Computer China Incidence Predictive Value of Tests Seasons Humans Brucellosis Models, Statistical
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Epidemiological Features of Human Brucellosis in Iran (2011-2018) and Prediction of Brucellosis with Data-Mining Models.

Journal of research in health sciences Dec 4, 2019
BACKGROUND: Brucellosis is known as the major zoonotic disease. We aimed to compare the performance of some data-mining models in predicting the monthly brucellosis cases in Iran.
Female Adult Animals Incidence Brucellosis Male Middle Aged Humans Iran Support Vector Machine Zoonoses Data Mining Models, Statistical Seasons
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A comparison of three data mining time series models in prediction of monthly brucellosis surveillance data.

Zoonoses and public health Jul 15, 2019
The early and accurately detection of brucellosis incidence change is of great importance for implementing brucellosis prevention strategic health planning. The present study investigated and compared the performance of the three data mining techniqu...
Data Mining Humans Zoonoses Animals Models, Statistical Brucellosis Population Surveillance Support Vector Machine Iran
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Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks.

BMC infectious diseases May 14, 2019
BACKGROUND: Establishing epidemiological models and conducting predictions seems to be useful for the prevention and control of human brucellosis. Autoregressive integrated moving average (ARIMA) models can capture the long-term trends and the period...
Incidence Brucellosis Models, Statistical Humans Neural Networks, Computer Seasons China Recurrence Jordan
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Improving human brucellosis susceptibility mapping using effective and simultaneously metaheuristic-based feature selection and hyperparameter tuning.

Acta tropica Jul 1, 2025
Human Brucellosis, a neglected zoonotic disease, affects 1.6 to 2.1 million people globally each year. In Iran, it has become a significant health concern, with an average annual incidence rate of 19.91 cases per 100,000 people. This study aims to cr...
Algorithms Brucellosis Iran Disease Susceptibility Humans Machine Learning
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