AI Medical Compendium Topic

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Image Interpretation, Computer-Assisted

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Graph neural networks in histopathology: Emerging trends and future directions.

Medical image analysis
Histopathological analysis of whole slide images (WSIs) has seen a surge in the utilization of deep learning methods, particularly Convolutional Neural Networks (CNNs). However, CNNs often fail to capture the intricate spatial dependencies inherent i...

Multi-scale feature fusion of deep convolutional neural networks on cancerous tumor detection and classification using biomedical images.

Scientific reports
In the present scenario, cancerous tumours are common in humans due to major changes in nearby environments. Skin cancer is a considerable disease detected among people. This cancer is the uncontrolled evolution of atypical skin cells. It occurs when...

Uncertainty Global Contrastive Learning Framework for Semi-Supervised Medical Image Segmentation.

IEEE journal of biomedical and health informatics
In semi-supervised medical image segmentation, the issue of fuzzy boundaries for segmented objects arises. With limited labeled data and the interaction of boundaries from different segmented objects, classifying segmentation boundaries becomes chall...

Attention-Guided 3D CNN With Lesion Feature Selection for Early Alzheimer's Disease Prediction Using Longitudinal sMRI.

IEEE journal of biomedical and health informatics
Predicting the progression from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is critical for early intervention. Towards this end, various deep learning models have been applied in this domain, typically relying on structural magnetic ...

TKR-FSOD: Fetal Anatomical Structure Few-Shot Detection Utilizing Topological Knowledge Reasoning.

IEEE journal of biomedical and health informatics
Fetal multi-anatomical structure detection in ultrasound (US) images can clearly present the relationship and influence between anatomical structures, providing more comprehensive information about fetal organ structures and assisting sonographers in...

Automated Quantification of HER2 Amplification Levels Using Deep Learning.

IEEE journal of biomedical and health informatics
HER2 assessment is necessary for patient selection in anti-HER2 targeted treatment. However, manual assessment of HER2 amplification is time-costly, labor-intensive, highly subjective and error-prone. Challenges in HER2 analysis in fluorescence in si...

A Trustworthy Curriculum Learning Guided Multi-Target Domain Adaptation Network for Autism Spectrum Disorder Classification.

IEEE journal of biomedical and health informatics
Domain adaptation has demonstrated success in classification of multi-center autism spectrum disorder (ASD). However, current domain adaptation methods primarily focus on classifying data in a single target domain with the assistance of one or multip...

Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading.

IEEE journal of biomedical and health informatics
Diabetic Retinopathy (DR) is a leading cause of vision loss around the world. To help diagnose it, numerous cutting-edge works have built powerful deep neural networks (DNNs) to automatically grade DR via retinal fundus images (RFIs). However, RFIs a...

Melanoma Breslow Thickness Classification Using Ensemble-Based Knowledge Distillation With Semi-Supervised Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Melanoma is considered a global public health challenge and is responsible for more than 90% deaths related to skin cancer. Although the diagnosis of early melanoma is the main goal of dermoscopy, the discrimination between dermoscopic images of in s...

Harmonic Wavelet Neural Network for Discovering Neuropathological Propagation Patterns in Alzheimer's Disease.

IEEE journal of biomedical and health informatics
Emerging researchindicates that the degenerative biomarkers associated with Alzheimer's disease (AD) exhibit a non-random distribution within the cerebral cortex, instead following the structural brain network. The alterations in brain networks occur...