BACKGROUND: Seasonal influenza is a major global public health concern, leading to escalated morbidity and mortality rates. Traditional early warning models rely on binary (0/1) classification methods, which issue alerts only when predefined threshol...
BACKGROUND: Hepatic encephalopathy (HE) contributes significantly to mortality among patients with liver cirrhosis. Early prediction of HE is essential for clinical decision-making, yet remains challenging-particularly in noncancer-related cirrhosis ...
Brain insulin action plays an important role in metabolic and cognitive health, but there is no biomarker available to assess brain insulin resistance in humans. Here, we developed a machine learning framework based on blood DNA methylation profiles ...
Journal of computer-aided molecular design
Aug 6, 2025
In light of the increasing interest in G9a's role in neuroscience, three machine learning (ML) models, that are time efficient and cost effective, were developed to support researchers in this area. The models are based on data provided by PubChem an...
Environmental monitoring and assessment
Aug 6, 2025
Crop classification during the early stages is challenging because of the striking similarity in spectral and texture features among various crops. To improve classification accuracy, this study proposes a novel fusion-based deep learning approach. T...
The essential need to identify the most informative sources of greenhouse gas emissions (climate change drivers) impacting the food security nexus in Africa requires a comprehensive and holistic approach. Machine learning method excels in the identif...
Advances in artificial intelligence and machine learning have revolutionised data analysis, including in the field of marine and fisheries sciences. However, many fisheries agencies manage sensitive or proprietary data that cannot be shared externall...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Aug 5, 2025
To achieve rapid, non-destructive detection of food quality indicators, this study introduces a novel method that combines near-infrared (NIR) spectroscopy with the Extreme learning machine (ELM) model. Eight spectral preprocessing methods and three ...
BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals with widespread environmental persistence and human exposure. Currently, no studies have used machine learning (ML) to predict depression based on PFAS exposure. This stud...
The geographical authentication of green specialty coffee is an economically sensitive analytical task that is not yet fully resolved. We used an innovative combination of proteomic profiling with linear discriminant analysis for the authentication o...
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