Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

A Study on Computer Aided Disease Analysis using Data Mining Technique


Affiliations
1 Department of Computer Science and Engineering, Oakland University, Rochester, United States
     

   Subscribe/Renew Journal


Data mining is used to discover knowledge in data and present it in a human-friendly form. It is the process of verifying large amounts of data that are routinely collected. Data mining is most useful for exploratory analysis because of the vital information present in large amounts of data. This is a joint effort between humans and computers. When describing your problems and goals, you can achieve the best results by balancing human expertise with the computer's search capabilities. To detect the disease, the patient must be subjected to various tests. However, the use of data processing technology should reduce the amount of inspection. This reduced check plays an important role in both time and performance. There are advantages and disadvantages to this technique. This analytical paper analyzes data processing techniques used to predict different types of diseases. This article reviews analytical papers primarily aimed at predicting cardiovascular disease, pluripotency, and breast cancer.


Keywords

Association Rules, Breast Cancer, Classification Clustering, Diabetes, And Heart Disease.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 196

PDF Views: 1




  • A Study on Computer Aided Disease Analysis using Data Mining Technique

Abstract Views: 196  |  PDF Views: 1

Authors

Naohiro Tawara
Department of Computer Science and Engineering, Oakland University, Rochester, United States
Tetsunori Kobayashi
Department of Computer Science and Engineering, Oakland University, Rochester, United States

Abstract


Data mining is used to discover knowledge in data and present it in a human-friendly form. It is the process of verifying large amounts of data that are routinely collected. Data mining is most useful for exploratory analysis because of the vital information present in large amounts of data. This is a joint effort between humans and computers. When describing your problems and goals, you can achieve the best results by balancing human expertise with the computer's search capabilities. To detect the disease, the patient must be subjected to various tests. However, the use of data processing technology should reduce the amount of inspection. This reduced check plays an important role in both time and performance. There are advantages and disadvantages to this technique. This analytical paper analyzes data processing techniques used to predict different types of diseases. This article reviews analytical papers primarily aimed at predicting cardiovascular disease, pluripotency, and breast cancer.


Keywords


Association Rules, Breast Cancer, Classification Clustering, Diabetes, And Heart Disease.