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Smartphone Colorimetric Sensor for Salivary Uric Acid µPad dataset
- Citation Author(s):
- Submitted by:
- Weiran Liu
- Last updated:
- Thu, 06/13/2024 - 00:31
- DOI:
- 10.21227/8ad0-mw22
- Data Format:
- Research Article Link:
- License:
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Abstract
This is the dataset related to the article "Machine-learning-based Colorimetric Sensor on Smarthone for Salivary Uric Acid Detection". The dataset contains two types of images. The first type is the full-sized image captured by the sensor, which is used to evaluate the performance of the ROI detection. The second type is the reaction area from artificial saliva and clinical samples, which is used to train and test machine-learning models.
This is the dataset for the article "Machine-learning-based Colorimetric Sensor on Smartphone for Salivary Uric Acid Detection". The naming of the artificial saliva dataset is in the form of "concentration(ppm)_sample id.jpg", and that of the clinical sample is "patient id_sample id_concentration(µM/L).jpg". The libraries used are opencv_Python and Scikit Learn. The smartphone model is on Git Hub.
