Abstract:
Predicting the impact of different factors on the patient’s health is as important as diagnosing diseases, especially when monitoring patients with chronic diseases. To p...Show MoreMetadata
Abstract:
Predicting the impact of different factors on the patient’s health is as important as diagnosing diseases, especially when monitoring patients with chronic diseases. To perform this by Artificial Intelligence (AI) methods, it is recommended to determine the features importance (FI) of data. There are a number of methods to evaluate FI. However, we can see a big variation in their results which is difficult to interpret. To solve this issue, we proposed new method which aim is minimizing the differences. Furthermore, to demonstrate the effectiveness of the proposed method we used the extracted FIs as weights of the weighted KNN and compared performances.
Published in: 2022 International Conference on Information Science and Communications Technologies (ICISCT)
Date of Conference: 28-30 September 2022
Date Added to IEEE Xplore: 14 June 2023
ISBN Information:
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- IEEE Keywords
- Index Terms
- Chronic Disease ,
- Cardiovascular Disease ,
- Important Characteristics ,
- Hybrid Method ,
- Impact Of Different Factors ,
- Logistic Regression ,
- Random Forest ,
- Decision Tree ,
- Machine Learning Methods ,
- K-nearest Neighbor ,
- Characteristic Scale ,
- Results Of Algorithm ,
- Obese People ,
- Artificial Intelligence Algorithms ,
- Accuracy Of Network ,
- Logistic Regression Method ,
- Logistic Regression Algorithm ,
- Decision Tree Method ,
- Gini Impurity
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Chronic Disease ,
- Cardiovascular Disease ,
- Important Characteristics ,
- Hybrid Method ,
- Impact Of Different Factors ,
- Logistic Regression ,
- Random Forest ,
- Decision Tree ,
- Machine Learning Methods ,
- K-nearest Neighbor ,
- Characteristic Scale ,
- Results Of Algorithm ,
- Obese People ,
- Artificial Intelligence Algorithms ,
- Accuracy Of Network ,
- Logistic Regression Method ,
- Logistic Regression Algorithm ,
- Decision Tree Method ,
- Gini Impurity
- Author Keywords