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Toward fair graph neural networks via real counterfactual samples
Graph neural networks (GNNs) have become pivotal in various critical decision-making scenarios due to their exceptional performance. However,...
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Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
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How clustering affects the convergence of decentralized optimization over networks: a Monte-Carlo-based approach
Decentralized algorithms have gained substantial interest owing to advancements in cloud computing, Internet of Things (IoT), intelligent...
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Enhancing SNV identification in whole-genome sequencing data through the incorporation of known genetic variants into the minimap2 index
MotivationAlignment of reads to a reference genome sequence is one of the key steps in the analysis of human whole-genome sequencing data obtained...
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DQMMBSC: design of an augmented deep Q-learning model for mining optimisation in IIoT via hybrid-bioinspired blockchain shards and contextual consensus
Single-chained blockchains are highly secure but cannot be scaled to larger IIoT (Internet of Industrial Things) network scenarios due to storage...
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Cancer mutationscape: revealing the link between modular restructuring and intervention efficacy among mutations
There is increasing evidence that biological systems are modular in both structure and function. Complex biological signaling networks such as gene...
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Enhancing OCT patch-based segmentation with improved GAN data augmentation and semi-supervised learning
For optimum performance, deep learning methods, such as those applied for retinal and choroidal layer segmentation in optical coherence tomography...
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Evolution of hadron therapy from 1935 to 2005: a personal view
IntroductionHadron therapy is today an established modality in cancer radiation therapy that, world-wide, is available in about hundred centres....
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The Multi-attribute impact of hyperlinks in blogs: an emotion-centric approach
As a digital social medium, blogs have transformed into arenas where individuals can express their perspectives, concepts, and feelings. This...
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HyperMatch: long-form text matching via hypergraph convolutional networks
Semantic text matching plays a vital role in diverse domains, such as information retrieval, question answering, and recommendation. However, longer...
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Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling
Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the...
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METASEED: a novel approach to full-length 16S rRNA gene reconstruction from short read data
BackgroundWith the emergence of Oxford Nanopore technology, now the on-site sequencing of 16S rRNA from environments is available. Due to the error...
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Improving laryngeal cancer detection using chaotic metaheuristics integration with squeeze-and-excitation resnet model
Laryngeal cancer (LC) represents a substantial world health problem, with diminished survival rates attributed to late-stage diagnoses. Correct...
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expHRD: an individualized, transcriptome-based prediction model for homologous recombination deficiency assessment in cancer
BackgroundHomologous recombination deficiency (HRD) stands as a clinical indicator for discerning responsive outcomes to platinum-based chemotherapy...
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Building RadiologyNET: an unsupervised approach to annotating a large-scale multimodal medical database
BackgroundThe use of machine learning in medical diagnosis and treatment has grown significantly in recent years with the development of...
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Anomaly analytics in data-driven machine learning applications
Machine learning is used widely to create a range of prediction or classification models. The quality of the machine learning (ML) models depends not...
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Temporal analysis of computational economics: a topic modeling approach
This study offers a comprehensive investigation into the thematic evolution within computational economics over the past two decades, leveraging...
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Characteristics of the Structural Connectivity in Patients with Brain Injury and Chronic Health Symptoms: A Pilot Study
Diffusion properties from diffusion tensor imaging (DTI) are exquisitely sensitive to white matter abnormalities incurred during traumatic brain...
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De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network
Counterfactual inference for continuous rather than binary treatment variables is more common in real-world causal inference tasks. While there are...
