AIMC Topic: Thailand

Clear Filters Showing 41 to 50 of 56 articles

Spatiotemporal Bayesian networks for malaria prediction.

Artificial intelligence in medicine
Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been use...

Artificial Neural Network and Genetic Algorithm Hybrid Intelligence for Predicting Thai Stock Price Index Trend.

Computational intelligence and neuroscience
This study investigated the use of Artificial Neural Network (ANN) and Genetic Algorithm (GA) for prediction of Thailand's SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an...

Fast and simple method for semiquantitative determination of calcium propionate in bread samples.

Journal of food and drug analysis
Calcium propionate has been widely used as a preservative in bakery and in bread. It is sometimes not carefully used, or a high concentration is added to preserve products. High consumption of calcium propionate can lead to several health problems. T...

Evidence of Water Quality Degradation in Lower Mekong Basin Revealed by Self-Organizing Map.

PloS one
To reach a better understanding of the spatial variability of water quality in the Lower Mekong Basin (LMB), the Self-Organizing Map (SOM) was used to classify 117 monitoring sites and hotspots of pollution within the basin identified according to wa...

Morbidity Rate Prediction of Dengue Hemorrhagic Fever (DHF) Using the Support Vector Machine and the Aedes aegypti Infection Rate in Similar Climates and Geographical Areas.

PloS one
BACKGROUND: In the past few decades, several researchers have proposed highly accurate prediction models that have typically relied on climate parameters. However, climate factors can be unreliable and can lower the effectiveness of prediction when t...

RhDnostics: A Machine Learning-Based Predictive Algorithm Model for RhD-Negative and DEL Blood Group Screening.

The journal of applied laboratory medicine
BACKGROUND: The D-elution (DEL) phenotype is serologically mislabeled as Rh-negative because of the very low amount of D antigen on red blood cells. The adsorption-elution test and genotyping are recommended tests for confirmation. However, turnaroun...

Machine learning-driven analysis of soil microplastic distribution in the Bang Pakong Watershed, Thailand.

Environmental pollution (Barking, Essex : 1987)
Microplastics (MPs) have emerged as a pervasive environmental pollutant due to their persistence and global distribution. However, MPs relationships with covariables remain largely unexplored. This study investigates factors influencing MPs occurrenc...

Determining mosquito age using surface-enhanced Raman spectroscopy and artificial neural networks: insights into the influence of origin and sex.

Parasites & vectors
BACKGROUND: Mosquito-borne diseases, such as malaria, dengue, and Zika, continue to pose significant threats to global health, resulting in millions of cases and thousands of deaths each year. Notably, only older mosquitoes can transmit these disease...

Comparison of spatial prediction models from Machine Learning of cholangiocarcinoma incidence in Thailand.

BMC public health
BACKGROUND: Cholangiocarcinoma (CCA) poses a significant public health challenge in Thailand, with notably high incidence rates. This study aimed to compare the performance of spatial prediction models using Machine Learning techniques to analyze the...