Physics-informed neural networks (PINNs) represent a transformative approach to data models by incorporating known physical laws into neural network training, thereby improving model generalizability, reduce data dependency, and enhance interpretabil...
The existing literature lacks a comprehensive analysis of the clinical evolution of septic patients, which is highly heterogeneous and patient-dependent. The aim of this study is to develop machine learning models capable of predicting the clinical e...
Sign language recognition (SLR) has the potential to bridge communication gaps and empower hearing-impaired communities. To ensure the portability and accessibility of the SLR system, its implementation on a portable, server-independent device become...
The rapid proliferation of online news demands robust automated classification systems to enhance information organization and personalized recommendation. Although traditional methods like TF-IDF with Naive Bayes provide foundational solutions, thei...
Capsule Networks (CapsNets) have demonstrated an enhanced ability to capture spatial relationships and preserve hierarchical feature representations compared to Convolutional Neural Networks (CNNs). However, the dynamic routing mechanism in CapsNets ...
This paper presents the findings of the research aimed at investigating the influence of visual content, posted on social media in shaping users' sentiments towards specific sociopolitical events. The study analyzed various sociopolitical topics by e...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 29, 2025
Accurate wound age estimation is of great significance in forensic practice. However, postmortem changes often obscure or even obliterate the biological information of skeletal muscle injuries, making it extremely challenging to accurately estimate t...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 29, 2025
Immunotherapy has revolutionized lung cancer treatment, yet predicting patient response remains a challenge. This study used Raman spectroscopy to differentiate between non-small-cell lung cancer patients with short-lasting and long-lasting responses...
Single nucleotide polymorphisms (SNPs) are widely used in precision medicine, disease predisposition assessment, nutrigenetics and authenticity testing of agricultural and food products. SNP genotyping is much more challenging than detecting longer D...
Accurately predicting the concentrations and spatial distribution of soil heavy metal(loid)s is crucial for effective environmental management and human health risk assessment. However, existing studies are often limited by poor model accuracy, featu...
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