AIMC Topic: Humans

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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...

Deep learning in 3D cardiac reconstruction: a systematic review of methodologies and dataset.

Medical & biological engineering & computing
This study presents an advanced methodology for 3D heart reconstruction using a combination of deep learning models and computational techniques, addressing critical challenges in cardiac modeling and segmentation. A multi-dataset approach was employ...

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...

Unlocking the diagnostic potential of electrocardiograms through information transfer from cardiac magnetic resonance imaging.

Medical image analysis
Cardiovascular diseases (CVD) can be diagnosed using various diagnostic modalities. The electrocardiogram (ECG) is a cost-effective and widely available diagnostic aid that provides functional information of the heart. However, its ability to classif...

Future of Artificial Intelligence-Machine Learning Trends in Pathology and Medicine.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Artificial intelligence (AI) and machine learning (ML) are transforming the field of medicine. Health care organizations are now starting to establish management strategies for integrating such platforms (AI-ML toolsets) that leverage the computation...

ARTIFICIAL INTELLIGENCE DEMONSTRATES POTENTIAL IN DETECTING CARIES ON BITEWING RADIOGRAPHS, BUT FURTHER HIGH-QUALITY STUDIES ARE REQUIRED.

The journal of evidence-based dental practice
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Diagnostic performance of artificial intelligence-aided caries detection on bitewing radiographs: A systematic review and meta-analysis. Ammar, N. & Kühnisch, J. Japanese Dental Science Review, 60(2024): 1...