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Quantum analysis of squiggle data
Squiggle data is the numerical output of DNA and RNA sequencing by the Nanopore next generation sequencing platform. Nanopore sequencing offers...
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Disclosing transcriptomics network-based signatures of glioma heterogeneity using sparse methods
Gliomas are primary malignant brain tumors with poor survival and high resistance to available treatments. Improving the molecular understanding of...
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STAR_outliers: a python package that separates univariate outliers from non-normal distributions
There are not currently any univariate outlier detection algorithms that transform and model arbitrarily shaped distributions to remove univariate...
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Machine learning based study for the classification of Type 2 diabetes mellitus subtypes
PurposeData-driven diabetes research has increased its interest in exploring the heterogeneity of the disease, aiming to support in the development...
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Assessment of emerging pretraining strategies in interpretable multimodal deep learning for cancer prognostication
BackgroundDeep learning models can infer cancer patient prognosis from molecular and anatomic pathology information. Recent studies that leveraged...
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Neural network-based prognostic predictive tool for gastric cardiac cancer: the worldwide retrospective study
BackgroundsThe incidence of gastric cardiac cancer (GCC) has obviously increased recently with poor prognosis. It’s necessary to compare GCC...
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Inverse problem for parameters identification in a modified SIRD epidemic model using ensemble neural networks
In this paper, we propose a parameter identification methodology of the SIRD model, an extension of the classical SIR model, that considers the...
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ChatGPT and large language models in academia: opportunities and challenges
The introduction of large language models (LLMs) that allow iterative “chat” in late 2022 is a paradigm shift that enables generation of text often...
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Overlap** filter bank convolutional neural network for multisubject multicategory motor imagery brain-computer interface
BackgroundMotor imagery brain-computer interfaces (BCIs) is a classic and potential BCI technology achieving brain computer integration. In motor...
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Comparison of cancer subtype identification methods combined with feature selection methods in omics data analysis
BackgroundCancer subtype identification is important for the early diagnosis of cancer and the provision of adequate treatment. Prior to identifying...
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ScInfoVAE: interpretable dimensional reduction of single cell transcription data with variational autoencoders and extended mutual information regularization
Single-cell RNA-sequencing (scRNA-seq) data can serve as a good indicator of cell-to-cell heterogeneity and can aid in the study of cell growth by...
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Changing word meanings in biomedical literature reveal pandemics and new technologies
While we often think of words as having a fixed meaning that we use to describe a changing world, words are also dynamic and changing. Scientific...
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A self-inspected adaptive SMOTE algorithm (SASMOTE) for highly imbalanced data classification in healthcare
In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease...
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Automated quantitative trait locus analysis (AutoQTL)
BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture...
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Reference-free phylogeny from sequencing data
MotivationClustering of genetic sequences is one of the key parts of bioinformatics analyses. Resulting phylogenetic trees are beneficial for solving...
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Algorithm-based detection of acute kidney injury according to full KDIGO criteria including urine output following cardiac surgery: a descriptive analysis
BackgroundAutomated data analysis and processing has the potential to assist, improve and guide decision making in medical practice. However, by now...
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Unsupervised encoding selection through ensemble pruning for biomedical classification
BackgroundOwing to the rising levels of multi-resistant pathogens, antimicrobial peptides, an alternative strategy to classic antibiotics, got more...
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Clinical assistant decision-making model of tuberculosis based on electronic health records
BackgroundTuberculosis is a dangerous infectious disease with the largest number of reported cases in China every year. Preventing missed diagnosis...
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Prediction of the risk of develo** end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms
ObjectivesType 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for...
