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  Published Paper Details:

  Paper Title

A Review on Diabetes Detection using machine learning techniques

  Authors

  Tarun Viswakarma,  Yavan Mahilang,  Yashwit Soni

  Keywords

Diabetes mellitus, Pancreas, Insulin, Blood sugar, Fasting blood sugar level, Type1 diabetes, Type2 diabetes, Causes of diabetes, Diagnosis of diabetes, Artificial intelligence, KNN, Support Vector Machine (SVM), Decision trees, Random Forest, Machine learning

  Abstract


Diabetes mellitus is a chronic disease that occurs as a result of the pancreas not producing enough insulin or the body's inability to use the insulin it produces effectively. Insulin is a drug that controls blood sugar. A fasting blood sugar level of 70-110 mg/dL is considered normal, 100-125 mg/dL is considered diabetes, and 126 mg/dL and above is considered diabetes. The number of people with diabetes increased from 108 million in 1980 to 422 million in 2014. The rate of increase was faster in low- and middle-income countries than in high-income countries. There are two types of diabetes - type1 diabetes and type2 diabetes. This section explains the causes of both types of diabetes. Diagnosis of diabetes: Many scientists and doctors are now developing artificial intelligence-based diagnostic methods to better solve problems caused by human error. KNN, Support Vector Machine (SVM), decision trees, Random Forest etc. Various types of machine learning are discussed and compared

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2305482

  Paper ID - 235646

  Page Number(s) - d644-d650

  Pubished in - Volume 11 | Issue 5 | May 2023

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Tarun Viswakarma,  Yavan Mahilang,  Yashwit Soni,   "A Review on Diabetes Detection using machine learning techniques", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 5, pp.d644-d650, May 2023, Available at :http://www.ijcrt.org/papers/IJCRT2305482.pdf

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ISSN: 2320-2882
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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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