AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Water Microbiology

Showing 11 to 20 of 33 articles

Clear Filters

Evaluation of a protocol for reducing the microbial contamination of dental unit water.

Acta odontologica latinoamericana : AOL
Biofilm on dental unit waterlines can spread microbial contamination in the water. The aim of this study was to investigate microbial contamination of water from supplies and dental units before and after the implementation of a protocol for microbia...

Predicting culturable enterococci exceedances at Escambron Beach, San Juan, Puerto Rico using satellite remote sensing and artificial neural networks.

Journal of water and health
Predicting recreational water quality is key to protecting public health from exposure to wastewater-associated pathogens. It is not feasible to monitor recreational waters for all pathogens; therefore, monitoring programs use fecal indicator bacteri...

Microbiome composition and implications for ballast water classification using machine learning.

The Science of the total environment
Ballast water is a vector for global translocation of microorganisms, and should be monitored to protect human and environmental health. This study utilizes high throughput sequencing (HTS) and machine learning to examine the bacterial and fungal mic...

An artificial neural network and Random Forest identify glyphosate-impacted brackish communities based on 16S rRNA amplicon MiSeq read counts.

Marine pollution bulletin
Machine learning algorithms can be trained on complex data sets to detect, predict, or model specific aspects. Aim of this study was to train an artificial neural network in comparison to a Random Forest model to detect induced changes in microbial c...

Rapid detection of microbiota cell type diversity using machine-learned classification of flow cytometry data.

Communications biology
The study of complex microbial communities typically entails high-throughput sequencing and downstream bioinformatics analyses. Here we expand and accelerate microbiota analysis by enabling cell type diversity quantification from multidimensional flo...

Predicting the concentration of total coliforms in treated rural domestic wastewater by multi-soil-layering (MSL) technology using artificial neural networks.

Ecotoxicology and environmental safety
Many indicators are involved in monitoring water quality. For instance, the fecal indicator bacteria are extremely important to detect the water quality. For this purpose, to better predict the total coliforms at the outlet of a Multi-Soil-Layering (...

Sequence-enabled community-based microbial source tracking in surface waters using machine learning classification: A review.

Journal of microbiological methods
The development of Microbial Source Tracking (MST) technologies was borne out of necessity. This was largely due to the: 1) inadequacies of the fecal indicator bacterial paradigm, 2) fact that many fecal bacteria can survive and often grow in the env...

Identification the source of fecal contamination for geographically unassociated samples with a statistical classification model based on support vector machine.

Journal of hazardous materials
The bacterial diversity and corresponding biological significance revealed by high-throughput sequencing contribute massive information to source tracking of fecal contamination. The performances of classification models on predicting the fecal sourc...

Improvement of DBR routing protocol in underwater wireless sensor networks using fuzzy logic and bloom filter.

PloS one
Routing protocols for underwater wireless sensor networks (UWSN) and underwater Internet of Things (IoT_UWSN) networks have expanded significantly. DBR routing protocol is one of the most critical routing protocols in UWSNs. In this routing protocol,...

Enhancing water quality prediction for fluctuating missing data scenarios: A dynamic Bayesian network-based processing system to monitor cyanobacteria proliferation.

The Science of the total environment
Tackling the impact of missing data in water management is crucial to ensure the reliability of scientific research that informs decision-making processes in public health. The goal of this study is to ascertain the root causes associated with cyanob...