Dear All, I am trying to apply data mining and machine learning techniques in diabetes prediction. Therefore, I need more data.
I understand that, there is a Pima indian and UCI database. But this not enough, what i need.
The required data can be
e.g., Age, sex, glucose, LDL, HDL, BMI, HbA1C and other variables and short and long term outcome of the subject. Outcome can be defined by good and poor outcome.The poor outcome can be chronic disease or CVD.
I would like to collaborate.
Your cooperation will be highly acknowledged.
Waiting to hearing from you.
Dear Md.abdul Awal,
Maybe you already know the following papers and data-link on the subject:
Kavakiotis I, Tsave O, Salifoglou A, Maglaveras N, Vlahavas I, Chouvarda I. Machine Learning and Data Mining Methods in Diabetes Research. Comput Struct Biotechnol J 2017;15:104-116. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5257026/pdf/main.pdf
White NH. Long-term Outcomes in Youths with Diabetes Mellitus. Pediatr Clin North Am 2015;62(4):889-909. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4662600/pdf/nihms737282.pdf
Nwosu BU, Zhang B, Ayyoub SS, Choi S, Villalobos-Ortiz TR, Alonso LC, Barton BA. Children with type 1 diabetes who experienced a honeymoon phase had significantly lower LDL cholesterol 5 years after diagnosis. PLoS One 2018;13(5):e0196912. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5955510/pdf/pone.0196912.pdf
Selected Trend Table from Health, United States, 2011. Diabetes prevalence and glycemic control among adults 20 years of age and over, by sex, age, and race and Hispanic origin: United States, selected years 1988 - 1994 through 2003 – 2006: https://catalog.data.gov/dataset/selected-trend-table-from-health-united-states-2011-diabetes-prevalence-and-glycemic-contr-63c3a
All the best for your research,
Martin
Hello,
which platform do you use?
What do you think, how much data would you need? If you could send the form with some data samples. There are probably some researches who could be interested (for diabetes mellitus)...
Best regards,
Sanja
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