Article-Journal

Parallel VMamba and Attention-Based Pneumonia Severity Prediction from CXRs: A Robust Model with Segmented Lung Replacement Augmentation
Background/Objectives: Rapid and accurate assessment of lung diseases, like pneumonia, is critical for effective clinical …
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PViTGAtt-IP: Severity Quantification of Lung Infections in Chest X-rays and CT Scans via Parallel and Cross-Attended Encoders
The development of a robust and adaptive deep learning technique for the diagnosis of pneumonia and the assessment of its severity was …
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Recognizing past shapes: sex differentiation through deep learning on European Upper Palaeolithic hand stencils
This study explores the application of advanced deep learning techniques in analyzing Upper Palaeolithic hand stencil representations, …
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Semi-supervised learning for multi-view and non-graph data using Graph Convolutional Networks
Semi-supervised learning with a graph-based approach has become increasingly popular in machine learning, particularly when dealing …
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The role of artificial intelligence in implant dentistry: a systematic review
The aim of this systematic review was to comprehensively analyse recent studies on the application of artificial intelligence (AI) in …
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Towards Dynamic Self-Training for Scalable Semi-Supervised Learning on Graphs
In the realm of graph-based semi-supervised learning (GSSL), traditional methodologies often struggle to effectively handle labeled …
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Unified multi-view data clustering: Simultaneous learning of consensus coefficient matrix and similarity graph
Integrating data from multiple sources or views has become increasingly common in data analysis, particularly in fields like …
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An End-to-End Approach for Graph-Based Multi-View Data Clustering
Clustering data from different sources or views is a key challenge in real-world applications. While traditional graph-based methods …
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Scalable and Inductive Semi-supervised Classifier with Sample Weighting Based on Graph Topology
Recently, graph-based semi-supervised learning (GSSL) has garnered significant interest in the realms of machine learning and pattern …
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A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features
Cellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a …
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