http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Iqra Javaid (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Iqra Javaid,Shahid Mehmood,Imran Ahmad,Muhammad Adnan Khan 한국차세대컴퓨팅학회 2023 한국차세대컴퓨팅학회 학술대회 Vol.2023 No.12
According to new WHO statistics, heart disease is the top reason of death worldwide, killing 17.9 million people each year. This is a growing number. One of the most wellknown issues in clinical offices is that no two professionals have the same knowledge and talent when serving their patients. Researchers are utilizing data mining and machine learning techniques to overcome these difficulties by using predictive analytics to anticipate the risk of heart problems. This study examines the accuracy of various machine learning methods, including Logistic Regression, Naive Bayes, Decision Trees, Support Vector Machines, Neural Networks, and Stochastic Gradient Descent in the prediction of heart disease based on various factors and symptoms such as gender, age, chest pain, and blood sugar using appropriate data. The research entails applying a typical data mining approach to accurately uncover relationships between numerous data sources to predict heart disease. These machine learning algorithms take less time and are more accurate at predicting heart illness, which will lower the global convergence of essential life.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
