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Modelling dataset bias in machine-learned theories of economic decision-making
Normative and descriptive models have long vied to explain and predict human risky choices, such as those between goods or gambles. A recent study...
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Transformative Deep Neural Network Approaches in Kidney Ultrasound Segmentation: Empirical Validation with an Annotated Dataset
Kidney ultrasound (US) images are primarily employed for diagnosing different renal diseases. Among them, one is renal localization and detection,...
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Beyond benchmarking and towards predictive models of dataset-specific single-cell RNA-seq pipeline performance
BackgroundThe advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the...
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Sample size determination for training set optimization in genomic prediction
Key messageA practical approach is developed to determine a cost-effective optimal training set for selective phenoty** in a genomic prediction...
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A panel dataset of COVID-19 vaccination policies in 185 countries
We present a panel dataset of COVID-19 vaccine policies, with data from 01 January 2020 for 185 countries and a number of subnational jurisdictions,...
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SpikeBALL: Neuromorphic Dataset for Object Tracking
Most of widely used datasets are not suitable for Spiking Neural Networks (SNNs) due to the need to encode the static data into spike trains and then...
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Deep ensemble approach for pathogen classification in large-scale images using patch-based training and hyper-parameter optimization
Pathogenic bacteria present a major threat to human health, causing various infections and illnesses, and in some cases, even death. The accurate...
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A Multi-view Molecular Pre-training with Generative Contrastive Learning
Molecular representation learning can preserve meaningful molecular structures as embedding vectors, which is a necessary prerequisite for molecular...
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A comparison of methods for training population optimization in genomic selection
Key messageMaximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A training set size of 50–55% (targeted) or...
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Investigating lexical categorization in reading based on joint diagnostic and training approaches for language learners
Efficient reading is essential for societal participation, so reading proficiency is a central educational goal. Here, we use an individualized...
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TBGA: a large-scale Gene-Disease Association dataset for Biomedical Relation Extraction
BackgroundDatabases are fundamental to advance biomedical science. However, most of them are populated and updated with a great deal of human effort....
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Multi-channel GCN ensembled machine learning model for molecular aqueous solubility prediction on a clean dataset
This study constructed a new aqueous solubility dataset and a solubility regression model which was ensembled by GCN and machine learning models....
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A self-supervised deep learning method for data-efficient training in genomics
Deep learning in bioinformatics is often limited to problems where extensive amounts of labeled data are available for supervised classification. By...
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Improving language model of human genome for DNA–protein binding prediction based on task-specific pre-training
The DNA–protein binding plays a pivotal role in regulating gene expression and evolution, and computational identification of DNA–protein has drawn...
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Molecular control of endurance training adaptation in male mouse skeletal muscle
Skeletal muscle has an enormous plastic potential to adapt to various external and internal perturbations. Although morphological changes in...
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Characterizing the impacts of dataset imbalance on single-cell data integration
Computational methods for integrating single-cell transcriptomic data from multiple samples and conditions do not generally account for imbalances in...
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CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice
BackgroundDue to the growing amount of COVID-19 research literature, medical experts, clinical scientists, and researchers frequently struggle to...
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AFD-Net: Apple Foliar Disease multi classification using deep learning on plant pathology dataset
BackgroundPlant diseases significantly affect the crop, so their identification is very important. Correct identification of these diseases is...
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Sexual dimorphism and the multi-omic response to exercise training in rat subcutaneous white adipose tissue
Subcutaneous white adipose tissue (scWAT) is a dynamic storage and secretory organ that regulates systemic homeostasis, yet the impact of endurance...
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A compressed large language model embedding dataset of ICD 10 CM descriptions
This paper presents novel datasets providing numerical representations of ICD-10-CM codes by generating description embeddings using a large language...
