AI Medical Compendium Topic

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

Agrochemicals

Showing 1 to 9 of 9 articles

Clear Filters

Chemical crystal identification with deep learning machine vision.

BMC research notes
OBJECTIVE: This study was carried out with the purpose of testing the ability of deep learning machine vision to identify microscopic objects and geometries found in chemical crystal structures.

Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.

Scientific reports
Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory approval and is an expensive and time-consuming process. The identification and utilization of early exposure gene signatures and robust predictive mo...

Nanotechnology and artificial intelligence to enable sustainable and precision agriculture.

Nature plants
Climate change, increasing populations, competing demands on land for production of biofuels and declining soil quality are challenging global food security. Finding sustainable solutions requires bold new approaches and integration of knowledge from...

Magnetic Biohybrid Robots as Efficient Drug Carrier to Generate Plant Cell Clones.

Small (Weinheim an der Bergstrasse, Germany)
Micro/nanorobots represent a new generation of micromachines that can accomplish various tasks, such as loading and transporting specific targets or pharmaceuticals for a given application. Biohybrid robots consisting of biological cells (bacteria, s...

Surface-enhanced Raman spectroscopy charged probes under inverted superhydrophobic platform for detection of agricultural chemicals residues in rice combined with lightweight deep learning network.

Analytica chimica acta
In this study, surface-enhanced Raman spectroscopy (SERS) charged probes and an inverted superhydrophobic platform were used to develop a detection method for agricultural chemicals residues (ACRs) in rice combined with lightweight deep learning netw...

Computational prediction of the metabolites of agrochemicals formed in rats.

The Science of the total environment
Today, computational tools for the prediction of the metabolite structures of xenobiotics are widely available and employed in small-molecule research. Reflecting the availability of measured data, these in silico tools are trained and validated prim...

Schistosomiasis transmission: A machine learning analysis reveals the importance of agrochemicals on snail abundance in Rwanda.

PLoS neglected tropical diseases
BACKGROUND: Schistosomiasis is an important snail-borne parasitic disease whose transmission is exacerbated by water resource management activities. In Rwanda, meeting the growing population's demand for food has led to wetlands reclamation for culti...

A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health.

Scientific reports
Pesticides and other synthetic agrochemicals play a critical role in emerging agricultural practices by enhancing crop productivity and protecting against pests and diseases. However, their widespread application has raised significant concerns about...