Biomedical and Health Sciences
Chronic wounds pose an ongoing health concern globally, largely due to the prevalence of conditions such as diabetes and leprosy's disease. The standard method of monitoring these wounds involves visual inspection by healthcare professionals, a practice that could present challenges for patients in remote areas with inadequate transportation and healthcare infrastructure. This has led to the development of algorithms designed for the analysis and follow-up of wound images, which perform image-processing tasks such as classification, detection, and segmentation.
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Raw data of 'Tetherless Multi-targeted Bioimpedance Device for Monitoring Peripheral Artery Disease Progression'
The dataset includes results from measurements of pulse signals from three different arteries using a commercial bioimpedance device mentioned in the paper, both using the conventional method and the proposed approach.
Moreover, the dataset encompasses simulated outcomes derived from HFSS (High-Frequency Structure Simulator), specifically investigating the impact of different plaque sizes on current induction at various frequencies.
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Endoscopic images of patients with AIG, type B gastritis, and CNAG were collected between January 1st, 2019 and March 1st, 2023. All endoscopic images were acquired by Olympus Evis Lucera 260/290 (Tokyo, Japan) and FUJIFILM EC-760RV/M (Tokyo, Japan). This dataset includes 3576 endoscopic images. Poor image quality, images of the pharynx, images of the esophageal region, and images of the duodenal region were excluded.
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BIMCV-COVID19+ dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G (IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).
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The provided dataset is created is created by using European Commission Rapid Alert System's data for Salmonella cases. The dataset composed by 5 variables and all data is providet in categorical format. it is possible to use the dataset predict the salmonella cases based on type of food, month, country and warmth.
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BIMCV-COVID19- dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of no COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G (IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).
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781 Views
BIMCV-COVID19+ dataset is a large dataset with chest X-ray images CXR (CR, DX) and computed tomography (CT) imaging of COVID-19 patients along with their radiographic findings, pathologies, polymerase chain reaction (PCR), immunoglobulin G (IgG) and immunoglobulin M (IgM) diagnostic antibody tests and radiographic reports from Medical Imaging Databank in Valencian Region Medical Image Bank (BIMCV).
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