Accurate identification and segmentation of brain tumors in Magnetic Resonance Imaging (MRI) images are critical for timely diagnosis and treatment. MRI is frequently used to diagnose these disorders; however medical professionals find it challenging...
This work introduces a hybrid computational approach in which degree-based topological descriptors are harnessed with the aid of advanced regression models and artificial neural networks (ANNs) to predict the crucial physicochemical properties of 17 ...
The pursuit of expressive and human-like music generation remains a significant challenge in the field of artificial intelligence (AI). While deep learning has advanced AI music composition and transcription, current models often struggle with long-t...
Universal differential equations (UDEs) are an emerging approach in biomedical systems biology, integrating physiology-driven mathematical models with machine learning for data-driven model discovery in areas where knowledge of the underlying physiol...
BACKGROUND: Depression is a mental health condition that affects millions of people worldwide. Although common, it remains difficult to diagnose due to its heterogeneous symptomatology. Mental health questionnaires are currently the most used assessm...
Environmental monitoring and assessment
Jul 31, 2025
This study evaluates the robustness of a previously developed calibration model for low-cost ozone sensors, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS). The model was deployed at a different site without retraining. It was tested in Pu...
Analytical methods : advancing methods and applications
Jul 31, 2025
The botanical origin of honey significantly impacts its nutritional composition, quality, and price. Traditional identification methods are often complex, require expensive equipment, and are time-consuming. This article proposes a rapid detection me...
The healthcare industry is transforming with the integration of the Internet of Medical Things (IoMT) with AI-powered networks for improved clinical connectivity and advanced monitoring capabilities. However, IoMT devices struggle with traditional ne...
The working state of rolling bearing severely affects the performance of industrial equipment. Addressing the issue of that the difficulty of incipient weak signals feature extraction influences the rolling bearing diagnosis accuracy, an efficient be...
The 3D structure of molecules contains a wealth of important information, but traditional 3DCNN-based methods fail to adequately address the transformations of rigid motions (rotation, translation, and mapping). Equivariant graph neural networks (EGN...
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