medical
We curated and release a real-world medical clinical dataset, namely MedCD, in the context of building generative artificial intelligence (AI) applications in the clinical setting. The MedCD dataset is one of the accomplishments from our longitudinal applied AI research and deployment in a tertiary care hospital in China. First, the dataset is real and comprehensive, in that it was sourced from real-world electronic health records (EHRs), clinical notes, lab examination reports and more.
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The Left Atrium2018 dataset was used in the 2018 Left Atrium Segmentation Challenge and has the following characteristics:
Data Content
Image Type: It consists of 154 three-dimensional gadolinium-enhanced magnetic resonance imaging (LGE-MRI) images, which is currently the largest cardiac LGE-MRI dataset in the world.
Label Information: It contains the relevant labels of the left atrium segmented by three medical experts.
Application Fields
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A dataset comprising a total of 21 individuals has been meticulously compiled, with 9 individuals identified as exhibiting Major Depressive Disorder (MDD) based on the outcomes derived from the PHQ-9 Questionnaire. The remaining 12 individuals in the dataset are classified as non-MDD.
The dataset encompasses diverse sensor data, including temperature measurements, SpO2 readings, pulse rates, and accelerometer data. It is important to note that all data points were collected within a controlled environment, ensuring reliability and consistency throughout the dataset.
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