DSpace Repository

An Optimization Approach to Improve Classification Performance in Cancer and Diabetes Prediction

Show simple item record

dc.contributor.author Islam, Ashraful
dc.contributor.author Ahmed, Eshtiak
dc.contributor.author Mahmud, Md. Swakshar
dc.contributor.author Hossain, Sabrina
dc.date.accessioned 2021-09-01T09:33:16Z
dc.date.available 2021-09-01T09:33:16Z
dc.date.issued 2019-04-04
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6094
dc.description.abstract There are many destructive diseases in the world which cause rapid death by taking time to affect such as cancer and diabetes. They take a lot of time to spread, thus they are curable or somewhat scalable to a great extent if they are diagnosed soon after introduced into the human body. Research shows that almost all type of cancer can be cured if they are detected in the early stage. It is also true for diabetes as they can be controlled if they are detected at the right time. So, a prediction technique that takes help from the computer and processes data from affected user to detect possible contamination can be a great tool for assisting both the doctors and patients with these diseases. A challenge in the process is that the detection accuracy has to be acceptable in order to make the system a reliable one. In this study, we have analyzed medical data using several classification algorithms in order to optimize classifier performance for cancer and diabetes prediction. en_US
dc.language.iso en_US en_US
dc.publisher IEEE en_US
dc.subject Diabetes Prediction en_US
dc.subject Optimization en_US
dc.subject AHRQ en_US
dc.title An Optimization Approach to Improve Classification Performance in Cancer and Diabetes Prediction en_US
dc.type Article en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace


Browse

My Account

Statistics