Prediction of Diabetes in Early Stage through Machine Learning
Journal Title: International Journal for Modern Trends in Science and Technology - Year 2024, Vol 10, Issue 9
Abstract
The goal of this project is to create a system that uses machine learning to forecast the early signs of diabetes. Diabetes is a widespread, long-term condition with serious health consequences, and spotting it early is key to managing it well and avoiding serious health issues. Yet, spotting diabetes early can be difficult because its early symptoms are often subtle and the risk factors can vary widely. This system uses machine learning techniques to examine health records and spot trends that suggest a person might be at risk for diabetes. By entering important health information like blood sugar levels, body mass index, age, and family history, the system can provide tailored predictions about a person's risk of getting diabetes. By thoroughly analyzing data and training its models, the system can accurately forecast diabetes risk, allowing for early action and changes in lifestyle to either prevent or slow down the disease's progression. The project is designed to support public health efforts by giving people and medical professionals a reliable method for spotting diabetes early and taking steps to intervene
Authors and Affiliations
K. Gopala Reddy, M. Madhuri, SK. Shabeena, P. Sivaraj Gopal, K. Y. Koteswararao
Keywords
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- EP ID EP747893
- DOI https://doi.org/10.46501/IJMTST1009014
- Views 42
- Downloads 0
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