AIMC Topic: Tuberculosis
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A GIS-Based Artificial Neural Network Model for Spatial Distribution of Tuberculosis across the Continental United States.
International journal of environmental research and public health
Jan 8, 2019
Despite the usefulness of artificial neural networks (ANNs) in the study of various complex problems, ANNs have not been applied for modeling the geographic distribution of tuberculosis (TB) in the US. Likewise, ecological level researches on TB inci...
Analysis of tuberculosis disease through Raman spectroscopy and machine learning.
Photodiagnosis and photodynamic therapy
Oct 22, 2018
We present the effectiveness of Raman spectroscopy (RS) in combination with machine learning for screening and analysis of blood sera collected from tuberculosis patients. Blood samples of 60 patients have confirmed active pulmonary tuberculosis and ...
Towards better prediction of Mycobacterium tuberculosis lineages from MIRU-VNTR data.
Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases
Jun 28, 2018
The determination of lineages from strain-based molecular genotyping information is an important problem in tuberculosis. Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing is a commonly used molecular genotyp...
Predicting treatment outcome of drug-susceptible tuberculosis patients using machine-learning models.
Informatics for health & social care
Feb 20, 2018
Tuberculosis (TB) is a deadly contagious disease and a serious global health problem. It is curable but due to its lengthy treatment process, a patient is likely to leave the treatment incomplete, leading to a more lethal, drug resistant form of dise...
Preliminary investigation of human exhaled breath for tuberculosis diagnosis by multidimensional gas chromatography - Time of flight mass spectrometry and machine learning.
Journal of chromatography. B, Analytical technologies in the biomedical and life sciences
Jan 4, 2018
Tuberculosis (TB) remains a global public health malady that claims almost 1.8 million lives annually. Diagnosis of TB represents perhaps one of the most challenging aspects of tuberculosis control. Gold standards for diagnosis of active TB (culture ...
Rapid and sensitive method for simultaneous determination of first-line anti-tuberculosis drugs in human plasma by HPLC-MS/MS: Application to therapeutic drug monitoring.
Tuberculosis (Edinburgh, Scotland)
Nov 24, 2017
First-line anti-tuberculosis drugs are playing vital roles for curbing rapid spread of tuberculosis. Multidrug therapies are commonly applied in clinical to achieve better treatment outcomes. However, drug resistance and adverse reactions come along ...
Acquaintance to Artificial Neural Networks and use of artificial intelligence as a diagnostic tool for tuberculosis: A review.
Tuberculosis (Edinburgh, Scotland)
Sep 20, 2017
Tuberculosis [TB] has afflicted numerous nations in the world. As per a report by the World Health Organization [WHO], an estimated 1.4 million TB deaths in 2015 and an additional 0.4 million deaths resulting from TB disease among people living with ...
A New Hybrid Model Using an Autoregressive Integrated Moving Average and a Generalized Regression Neural Network for the Incidence of Tuberculosis in Heng County, China.
The American journal of tropical medicine and hygiene
Aug 18, 2017
It is a daunting task to eradicate tuberculosis completely in Heng County due to a large transient population, human immunodeficiency virus/tuberculosis coinfection, and latent infection. Thus, a high-precision forecasting model can be used for the p...
A Belief Rule Based Expert System to Assess Tuberculosis under Uncertainty.
Journal of medical systems
Jan 30, 2017
The primary diagnosis of Tuberculosis (TB) is usually carried out by looking at the various signs and symptoms of a patient. However, these signs and symptoms cannot be measured with 100 % certainty since they are associated with various types of unc...
Hybrid methodology for tuberculosis incidence time-series forecasting based on ARIMA and a NAR neural network.
Epidemiology and infection
Jan 24, 2017
Tuberculosis (TB) affects people globally and is being reconsidered as a serious public health problem in China. Reliable forecasting is useful for the prevention and control of TB. This study proposes a hybrid model combining autoregressive integrat...
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