Environmental monitoring and assessment
Jan 3, 2026
Artificial neural networks (ANNs) are widely applied in air quality modelling because they can capture nonlinear interactions among pollutants and support reliable air pollutant index (API) forecasting. This study aims to identify the pollutants that...
Journal of chemical information and modeling
Dec 27, 2025
This study integrates principal component analysis (PCA) with random forest (RF) modeling to present an enhanced machine learning framework for predicting gas-phase vacuum ultraviolet/ultraviolet (VUV/UV) absorption spectra. This method overcomes a s...
Effective weed detection for precise management remains a pertinent issue in modern agriculture. In this study, hyperspectral imaging (HSI) was combined with machine learning (ML) to differentiate between peanut plants and four common weeds found in ...
Plastic and paper foreign materials in tobacco shreds mainly originate from tobacco processing and packaging. These materials are highly similar to tobacco shreds in color and size, making them difficult for traditional machine vision systems to dete...
Accurate nitrogen management in rice (Oryza sativa L.) is essential for optimizing both crop productivity and environmental sustainability. This study evaluated the potential of Near-Infrared Spectroscopy (NIRS) combined with chemometric modeling to ...
Alzheimer's Disease (AD) is a very common neurodegenerative disorders and early detection using electroencephalography (EEG) can enable timely intervention, however, existing computational models often lack robustness, interpretability, and clinical ...
Journal of chemical information and modeling
Dec 14, 2025
Predicting essential oil yield in supercritical CO (SC-CO) extraction remains difficult due to variations in plant composition and process conditions. Conventional models often assume uniform feedstock behavior, which limits their applicability acros...
The rising prevalence of retinal diseases is a significant concern, as certain untreated conditions can lead to severe vision impairment or even blindness. Deep learning algorithms have emerged as a powerful tool for the diagnosis and analysis of med...
Brain tumor segmentation from MRI's and PET has always been a challenging and time-consuming phase for radiologists, due to low sensitivity boundary region pixels in this image modality. Deep learning-based image segmentation is the hot research topi...
Journal of nuclear medicine technology
Dec 3, 2025
The aim of the study was to validate a new method for semiautomatic subtraction of [Tc]Tc-sestamibi and [Tc]NaTcO SPECT 3-dimensional datasets using principal component analysis (PCA) against the results of parathyroid surgery and to compare its perf...
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