A Cloud IoT Based Framework for Diabetes Prediction

dc.contributor.authorSharma, Neha
dc.contributor.supervisorSingh, Ashima
dc.date.accessioned2018-07-31T09:39:37Z
dc.date.available2018-07-31T09:39:37Z
dc.date.issued2018-07-31
dc.descriptionMaster of Engineering- Softwareen_US
dc.description.abstractA healthcare system using modern computing techniques is the highest explored area in healthcare research. Researchers in the field of computing and healthcare are persistently working together to make such systems more technology ready. Recent studies by World Health Organization have shown an increment in the number of diabetic patients and their deaths. Diabetes is one of the basic sicknesses which have long-haul complexities related to it. A high volume of medical information is produced. It is important to gather, store, learn and predict the health of such patients using continuous monitoring and technological innovations. An alarming increase in the number of diabetic patients in India has become an important area of concern. With the assistance of innovation, it is important to construct a framework that store and examine the diabetic information and further see conceivable dangers. Its early detection and analysis remain a challenge among researchers. In this research, a prosperous/advanced and skillful method is presented in this research including IoT to gain a better result from the diabetic dataset. The proposed system is evaluated using “Pima Indians Diabetes” data seten_US
dc.identifier.urihttp://hdl.handle.net/10266/5126
dc.language.isoenen_US
dc.subjectClouden_US
dc.subjectIOTen_US
dc.subjectMachine Learningen_US
dc.subjectDiabetesen_US
dc.titleA Cloud IoT Based Framework for Diabetes Predictionen_US
dc.typeThesisen_US

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Neha Sharma_801631015.pdf
Size:
1.99 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
2.03 KB
Format:
Item-specific license agreed upon to submission
Description: