Diabetes prediction using machine learning and explainable AI techniques
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Abstract
Globally, diabetes affects 537 million people, making it the deadliest and the most common non-communicable disease. Many factors can cause a person to get affected by diabetes, like excessive body weight, abnormal cholesterol level, family history, physical inactivity, bad food habit etc. Increased urination is one of the most common symptoms of this disease. People with diabetes for a long time can get several complications like heart disorder, kidney disease, nerve damage, diabetic retinopathy etc. But its risk can be reduced if it is predicted early. In this paper, an automatic diabetes prediction system has been developed using a private dataset of female patients in Bangladesh and various machine…
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294
total citations
- FWCI
- 67.72
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- 100%
- References
- 24
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Authors
4Topics & keywords
Topics
Keywords
- Artificial intelligence
- Machine learning
- Computer science
- Random forest
- Decision tree
- Support vector machine
- Diabetes mellitus
- Gradient boosting
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