Artificial Intelligence
While deep learning has catalyzed breakthroughs across numerous domains, its broader adoption in clinical settings is inhibited by the costly and time-intensive nature of data acquisition and annotation. To further facilitate medical machine learning, we present an ultrasound dataset of 10,223 Brightness-mode (B-mode) images consisting of sagittal slices of porcine spinal cords (N=25) before and after a contusion injury.
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The removal of surgical tools from the brain is a critical aspect of post-operative care. Surgical sponges such as cotton balls are one of the most commonly retained tools, as they become visually indistinguishable from the surrounding brain tissue when soaked with blood and can fragment into smaller pieces. This can lead to life-threatening immunological responses and invasive reoperation, demonstrating the need for new foreign body object detection methods.
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Modern automotive embedded systems include a large number of electronic control units (ECU) responsible for managing sophisticated systems such as engine control, ABS brake systems, traction control, and power steering systems. To ensure the reliability and effectiveness of these functions, it is essential to apply rigorous test approaches and standards. The integration of diagnostic functions in automotive embedded systems demands consistent tests and a detailed analysis of data.
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Animal habitat surveys play a critical role in preserving the biodiversity of the land. One of the effective ways to gain insights into animal habitats involves identifying animal footprints, which offers valuable information about species distribution, abundance, and behavior.
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Data sources of MKG with structured medical knowledge database and unstructured scientific publications
Source Type
Name
Related researches
Structured medical knowledge database
KEGG
[20]
SIDER
[21]
ICD-10
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The dataset aims to compile images of buildings with structural damage for analysis. The images can be classified by the severity of damage to building facades after seismic events using deep learning techniques, particularly pre-trained convolutional neural networks and transfer learning. The analysis can precisely identify structural damage levels, aiding in effective evaluation and response strategies.
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The Defect Tracking dataset provides a comprehensive resource for software maintenance and defect prediction research. This dataset, downloaded from the Jira Spring website, includes detailed defect data from a variety of Spring application projects such as Spring Framework, Spring Boot, Spring Security, Spring Data, and others. It encompasses numerous attributes, including issue summaries, types, statuses, priorities, resolution details, and additional relevant information.
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This is the MRI scan database used in the research work of classifying Meningioma Tumor in humans by using hybrid Ensemble Deep Learning Network AlGoRes. It consist of two sets; one for training and another one for testing the Deep Learning Network AlGoRes.
Training data set consist of 822 imagers with meningioma_tumor and 395 images without tumor.
Testing data set consist of 115 imagers with meningioma_tumor and 104 images without tumor.
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This study utilizes the annual loan ledger data obtained from a commercial bank located in Jiangsu Province, China, which is called ChinaZJB. The ChinaZJB dataset consists of 1,329 valid samples of SMEs after merging the non-financial behavioral information and soft information on credit rating with the financial information, loan information, and non-financial basic information found in the annual loan ledger data.
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This large dataset includes six small datasets, including two types, one contains the original node relationship information and node feature information, please use it through the common network construction methods; the other is the dataset which has been processed, including the direct edge information and node's association information, which can be used to construct the network directly through the network construction methods.
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