AIMC Topic: Neural Networks, Computer

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A hybrid framework for colorectal cancer detection and U-Net segmentation using polynetDWTCADx.

Scientific reports
"PolynetDWTCADx" is a sophisticated hybrid model that was developed to identify and distinguish colorectal cancer. In this study, the CKHK-22 dataset, comprising 24 classes, served as the introduction. The proposed method, which combines CNNs, DWTs, ...

Preparation and optimisation of solid lipid nanoparticles of rivaroxaban using artificial neural networks and response surface method.

Journal of microencapsulation
AIMS: This study aimed to improve rivaroxaban delivery by optimising solid lipid nanoparticles (SLN) for minimal mean diameter and maximal entrapment efficiency (EE), enhancing solubility, bioavailability, and the ability to cross the blood-brain bar...

Prediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.

Medical physics
BACKGROUND: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increase the dose received by organs at risk. This can be addressed by real-time tracking, where respiration motion prediction is currently required to comp...

Automated ultrasonography of hepatocellular carcinoma using discrete wavelet transform based deep-learning neural network.

Medical image analysis
This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatocellular carcinoma (HCC) from abdominal ultrasound (US) images using artificial neural networks. The HCC-Net integrates the discrete wavelet transform (...

Dual-path neural network extracts tumor microenvironment information from whole slide images to predict molecular typing and prognosis of Glioma.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Utilizing AI to mine tumor microenvironment information in whole slide images (WSIs) for glioma molecular subtype and prognosis prediction is significant for treatment. Existing weakly-supervised learning frameworks based on...

User preference interaction fusion and swap attention graph neural network for recommender system.

Neural networks : the official journal of the International Neural Network Society
Recommender systems are widely used in various applications. Knowledge graphs are increasingly used to improve recommendation performance by extracting valuable information from user-item interactions. However, current methods do not effectively use ...

Multi-level feature fusion networks for smoke recognition in remote sensing imagery.

Neural networks : the official journal of the International Neural Network Society
Smoke is a critical indicator of forest fires, often detectable before flames ignite. Accurate smoke identification in remote sensing images is vital for effective forest fire monitoring within Internet of Things (IoT) systems. However, existing dete...

Convergence analysis of deep Ritz method with over-parameterization.

Neural networks : the official journal of the International Neural Network Society
The deep Ritz method (DRM) has recently been shown to be a simple and effective method for solving PDEs. However, the numerical analysis of DRM is still incomplete, especially why over-parameterized DRM works remains unknown. This paper presents the ...

DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusion MRI, namely DDEvENet, for anatomical brain parcellation. The key innovation of DDEvENet is the design of an evidential deep learning framework to q...