Health

The Comprehensive Patient-Health Monitoring Dataset is an extensive collection of health-related data gathered from remote monitoring systems between June 4, 2023, and October 4, 2023. This dataset comprises 10,000 samples, each meticulously recorded at ten-minute intervals, capturing a diverse array of vital signs and health metrics crucial for patient care and medical research.

Categories:
74 Views

We sourced our data by crawling comments from the “Zoufan” blog within the Weibo social platform. Subsequently, a team of qualified psychologists were enlisted to annotate the data. In our study, strict data preprocessing measures were adopted to protect users’ privacy.

SocialCD-3K (Cognitive Distortion Classification)

Categories:
306 Views

We sourced our data by crawling comments from the “Zoufan” blog within the Weibo social platform. Subsequently, a team of qualified psychologists were enlisted to annotate the data. In our study, strict data preprocessing measures were adopted to protect users’ privacy.

SOS-HL-1K (Suicide Risk Classification)

Categories:
92 Views

Wild-SHARD presents a novel Human Activity Recognition (HAR) dataset collected in an uncontrolled, real-world (wild) environment to address the limitations of existing datasets, which often need more non-simulated data. Our dataset comprises a time series of Activities of Daily Living (ADLs) captured using multiple smartphone models such as Samsung Galaxy F62, Samsung Galaxy A30s, Poco X2, One Plus 9 Pro and many more. These devices enhance data variability and robustness with their varied sensor manufacturers.

Categories:
122 Views

This dataset comprises a comprehensive collection of augmented MRI images of brain tumors, organized into two distinct folders: 'Yes' and 'No'. The 'Yes' folder contains 9,828 images of brain tumors, while the 'No' folder includes 9,546 images that do not exhibit brain tumors, resulting in a total of 19,374 images. All images are in PNG format, ensuring high-quality and consistent resolution suitable for various machine learning and medical imaging research applications.

Categories:
384 Views

This dataset consists of 462 field of views of Giemsa(dye)-stained and field(dye)-stained thin blood smear images acquired using an iPhone 10 mobile phone with a 12MP camera. The phone was attached to an Olympus microscope with 1000× objective lens. Half of the acquired images are red blood cells with a normal morphology and the other half have a Rouleaux formation morphology.

Categories:
323 Views

This dataset comprises 1718 annotated images extracted from 29 video clips recorded during Endoscopic Third Ventriculostomy (ETV) procedures, each captured at a frame rate of 25 FPS. Out of these images, 1645 are allocated for the training set, while the remainder is designated for the testing set. The images contain a total of 4013 anatomical or intracranial structures, annotated with bounding boxes and class names for each structure. Additionally, there are at least three language descriptions of varying technicality levels provided for each structure.

Categories:
301 Views

Early detection of kidney illness can be achieved by training machine learning algorithms to discover patterns in patient data, such as imaging, test results, and medical history. This will enable rapid diagnosis and start of treatment regimens, which can improve patient outcomes. With 98.97% accuracy in CKD detection, the suggested TrioNet with KNN imputer and SMOTE fared better than other models. This comprehensive research highlights the model's potential as a useful tool in the diagnosis of chronic kidney disease (CKD) and highlights its capabilities.

Categories:
410 Views

This study presents a comprehensive dataset to analyze risk factors associated with cardiovascular disease. The dataset comprises various patient attributes, including gender, age, total cholesterol, HDL (high-density lipoprotein), triglycerides, non-HDL (non-high-density lipoprotein), NIH-Equ-2, and direct LDL (low-density lipoprotein). These attributes comprise 25,991 patient data, robustly representing a large population sample.

Categories:
135 Views

Pages