International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Machine Learning-Based Approach for Diabetes |
|---|---|
| ABSTRACT | Diabetes which is the on-going illness that may impacts large number of people over the world ,and sadly the large number of people living with it and also it keeps on increasing day by day. Basically the diabetes impacts how the body may controls the blood sugar, commonly resulting in high blood sugar. One of the ways diabetes can first show itself is through simple daily changes constant thirst, unusual hunger or frequent bathroom visits. Poorly managed diabetes can take a heavy toll on health, causing complications such as a kidney damage, heart disease and vision problems and in worst cases even amputation. The body usually relies on insulin a hormone that works like a key to let glucose move from the blood into the cells where its converted into energy. In diabetes the process breaks down the pancreases may not produce enough insulin ,or the body may no longer respond to it properly. There are several types of diabetes. Type1 usually shows up earlier in life type is more common in adults and gestational diabetes can develop while a woman in pregnant. Manage diabetes isn’t always easy but technology is bringing new hope. Today Artificial Intelligence can scan through large sets of health data and pick up on patterns that might escape doctors, leading to quicker diagnosis and more personalized care. |
| AUTHOR | NISHUTHA M S, CHINNASWAMY C N, RAMPUR SRINATH Department of ISE, National Institute of Engineering, Mysuru, Karnataka, India Associate Professor, Department of ISE, National Institute of Engineering, Mysuru, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401062 |
| pdf/62_Machine Learning-Based Approach for Diabetes.pdf | |
| KEYWORDS | |
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