A Deep learning model for collective disorder using Visual Geometry Group 16
| dc.contributor.author | V RAVI RAJ : UJWAL V : SACHETH N K | |
| dc.date.accessioned | 2024-10-29T06:40:57Z | |
| dc.date.available | 2024-10-29T06:40:57Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | In the current scenario, people have become vulnerable to various diseases due to their lifestyle and their environment. Many of the analyses that have already been done looked at specific diseases. A user needs to use one analysis when they want to analyse diabetes, and another analysis when they want to analyse heart disease. This process takes a while. Moreover, if any user having multiple diseases, but the current method can only anticipate one disease, there is a potential that the death rate may rise as a result of the inability to foresee the other diseases. It is feasible to predict multiple diseases simultaneously using a multi disease model. Hence Users do not need to navigate numerous models in order to predict diseases. Time will be cut short, and there is a likelihood that fatality rates will go down because it can predict several diseases at once. | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/15992 | |
| dc.language.iso | en | |
| dc.publisher | NHCE | |
| dc.title | A Deep learning model for collective disorder using Visual Geometry Group 16 | |
| dc.type | Learning Object |