Urinalysis Test Results

Urinalysi test results of a local clinic in the Philippines

Source

This dataset was collected from a local clinic in Northern Mindanao, Philippines, and is from April of 2020 to January of 2023. If you are going to use this dataset for further analysis or related research, please cite our work. I would greatly appreciate it.

About

This dataset was collected for the fulfilment of the researchers capstone entitled: Optimizing UTI Diagnosis with Machine Learning and Artificial Neural Network for Reducing Misdiagnoses by Agdeppa et al. (2023). If you wish to acquire the research paper, please message me on my LinkedIn Account: https://tinyurl.com/54nnt2ea

Content

Age (The age of the patient) Note: Some patients are months old, so the age of these patients are preprocessed by dividing it by a hundred) e.g, 8 MONTHS OLD, 8/100 = 0.08
Gender (The gender of the patient) Note: Either male or female
Color (urine color)
Transparency (urine transparency)
Glucose (glucose is a type of sugar, and its presence in the urine can be an important indicator of certain health conditions)
Protein (the presence of protein in the urine is one of the parameters examined to assess kidney function and detect potential)
pH (the pH level measures the acidity or alkalinity of urine)
Specific Gravity (urine specific gravity is a measure of the concentration of particles in urine compared to water)
WBC (White Blood Cells) Note: Also known as leukocytes, white blood cells are a crucial part of the immune system
RBC (Red Blood Cells) Note: RBC are responsible for carrying oxygen throughout the body
Epithelial Cells (epithelial cells are cells that line the surfaces and cavities of the body, including the urinary tract)
Mucous Threads (mucous threads are strands of mucus that can be present in urine)
Amorphous Urates (amorphous urates are non-crystalline formations in the urine that consist of uric acid)
Bacteria (presence of bacteria in the urine)
Diagnosis (UTI Diagnosis) Note: Either NEGATIVE or POSITIVE

Acknowledgements

I would like to thank Jan Laurence Virtudez for helping and assisting the researchers gather the data from the local clinic. Moreover, I would also like to thank the University of Science and Technology of Southern Philippines, Cagayan de Oro (USTP - CDO) (Ms. Angelie P. Sabanal and Mr. Romen Samuel Wabina, MSc) for the help they provided.

Felt	Verdi
Data sist oppdatert	8. oktober 2024
Metadata sist oppdatert	8. oktober 2024
Opprettet	8. oktober 2024
Format	ZIP
Lisens	Creative Commons Attribution
Datastore active	False
Has views	False
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Mimetype	application/zip
Package id	697efc11-0d32-499b-86e7-c83177ca94c7
Position	0
Size	17,7 KiB
State	active
Url type	upload

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