AI Medical Compendium Topic

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

Pesticides

Showing 41 to 50 of 59 articles

Clear Filters

Averting robo-bees: why free-flying robotic bees are a bad idea.

Emerging topics in life sciences
Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduc...

Electrochemical inhibition bacterial sensor array for detection of water pollutants: artificial neural network (ANN) approach.

Analytical and bioanalytical chemistry
This work reports on further development of an inhibition electrochemical sensor array based on immobilized bacteria for the preliminary detection of a wide range of organic and inorganic pollutants, such as heavy metal salts (HgCl, PbCl, CdCl), pest...

Highly Sensitive Detection of Chemically Modified Thio-Organophosphates by an Enzymatic Biosensing Device: An Automated Robotic Approach.

Sensors (Basel, Switzerland)
Pesticides represent some of the most common man-made chemicals in the world. Despite their unquestionable utility in the agricultural field and in the prevention of pest infestation in public areas of cities, pesticides and their biotransformation p...

Prediction of Soil Adsorption Coefficient in Pesticides Using Physicochemical Properties and Molecular Descriptors by Machine Learning Models.

Environmental toxicology and chemistry
The soil adsorption coefficient (K ) plays an important role in environmental risk assessment of pesticide registration. Based on this risk assessment, applied and registered pesticides can be allowed in the European Union. Almost 1 yr is required to...

Data mining for pesticide decontamination using heterogeneous photocatalytic processes.

Chemosphere
Pesticides are chemical compounds used to kill pests and weeds. Due to their nature, pesticides are potentially toxic to many organisms, including humans. Among the various methods used to decontaminate pesticides from the environment, the heterogene...

In silico prediction of chemical acute contact toxicity on honey bees via machine learning methods.

Toxicology in vitro : an international journal published in association with BIBRA
In recent years, the decline of honey bees and the collapse of bee colonies have caught the attention of ecologists, and the use of pesticides is one of the main reasons for the decline. Therefore, ecological risk assessment of pesticides is essentia...

Trace Identification and Visualization of Multiple Benzimidazole Pesticide Residues on Leaves Using Terahertz Imaging Combined with Deep Learning.

International journal of molecular sciences
Molecular spectroscopy has been widely used to identify pesticides. The main limitation of this approach is the difficulty of identifying pesticides with similar molecular structures. When these pesticide residues are in trace and mixed states in pla...

A deep learning model to detect novel pore-forming proteins.

Scientific reports
Many pore-forming proteins originating from pathogenic bacteria are toxic against agricultural pests. They are the key ingredients in several pesticidal products for agricultural use, including transgenic crops. There is an urgent need to identify no...

Portable Deep Learning-Driven Ion-Sensitive Field-Effect Transistor Scheme for Measurement of Carbaryl Pesticide.

Sensors (Basel, Switzerland)
This research proposes a multiple-input deep learning-driven ion-sensitive field-effect transistor (ISFET) scheme to predict the concentrations of carbaryl pesticide. In the study, the carbaryl concentrations are varied between 1 × 10-1 × 10 M, and t...