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WLCD: a dataset of lifestyle in relation with women’s cancer
ObjectivesSocial media text mining has been widely used to extract information about the experiences and needs of patients regarding various...
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PmWebSpec: An Application to Create and Manage CDISC-Compliant Pharmacometric Analysis Dataset Specifications
A well-documented pharmacometric (PMx) analysis dataset specification ensures consistency in derivations of the variables, naming conventions,...
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HumanBrainAtlas: an in vivo MRI dataset for detailed segmentations
We introduce HumanBrainAtlas, an initiative to construct a highly detailed, open-access atlas of the living human brain that combines high-resolution...
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Machine Learning in the Parkinson’s disease smartwatch (PADS) dataset
The utilisation of smart devices, such as smartwatches and smartphones, in the field of movement disorders research has gained significant attention....
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Dataset on infant mortality rates in Brazil
ObjectivesSurveillance of infant and fetal deaths is of paramount importance in thinking about government strategies to reduce these rates, provide...
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HUST bearing: a practical dataset for ball bearing fault diagnosis
ObjectivesThe rapid growth of machine learning methods has led to an increase in the demand for data. For bearing fault diagnosis, the data...
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A panoptic segmentation dataset and deep-learning approach for explainable scoring of tumor-infiltrating lymphocytes
Tumor-Infiltrating Lymphocytes (TILs) have strong prognostic and predictive value in breast cancer, but their visual assessment is subjective. To...
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ITC-Net-blend-60: a comprehensive dataset for robust network traffic classification in diverse environments
ObjectivesRecognition of mobile applications within encrypted network traffic holds considerable effects across multiple domains, encompassing...
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LieWaves: dataset for lie detection based on EEG signals and wavelets
This study introduces an electroencephalography (EEG)-based dataset to analyze lie detection. Various analyses or detections can be performed using...
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Dataset development of pre-formulation tests on fast disintegrating tablets (FDT): data aggregation
ObjectivesTablet manufacturing development is costly, laborious, and time-consuming. Technologies related to artificial intelligence like ,predictive...
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ColonGen: an efficient polyp segmentation system for generalization improvement using a new comprehensive dataset
Colorectal cancer (CRC) is one of the most common causes of cancer-related deaths. While polyp detection is important for diagnosing CRC, high miss...
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State of nutrition amongst US college students: dataset of a national survey study
ObjectiveThis article presents the dataset titled “Nutrition habits amongst college students in the United States. [
1 ]” The dataset contains the... -
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Dataset for vaginal human papillomavirus infection among adolescent and early adult girls in Jos, Nigeria
ObjectivesTo assess risk factors for HPV infection, determine knowledge about HPV vaccines, assess willingness to receive the HPV vaccine among...
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Deep learning model fusion improves lung tumor segmentation accuracy across variable training-to-test dataset ratios
This study aimed to investigate the robustness of a deep learning (DL) fusion model for low training-to-test ratio (TTR) datasets in the segmentation...
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Multiple-source distribution deep adaptive feature norm network for EEG emotion recognition
Electroencephalogram (EEG) emotion recognition plays an important role in human–computer interaction, and a higher recognition accuracy can improve...
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Dataset for classifying and estimating the position, orientation, and dimensions of a list of primitive objects
ObjectivesRobotic systems are moving toward more interaction with the environment, which requires improving environmental perception methods. The...
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MAGPIE: accurate pathogenic prediction for multiple variant types using machine learning approach
Identifying pathogenic variants from the vast majority of nucleotide variation remains a challenge. We present a method named Multimodal Annotation...
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AVD-YOLOv5: a new lightweight network architecture for high-speed aortic valve detection from a new and large echocardiography dataset
AbstractHeart disease detection is currently gaining widespread attention as a means to enhance the accuracy of cardiologists’ diagnoses from cardiac...
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Identification of autism spectrum disorder using multiple functional connectivity-based graph convolutional network
Presently, the combination of graph convolutional networks (GCN) with resting-state functional magnetic resonance imaging (rs-fMRI) data is a...
