Association rule mining to detect factors which contribute to heart disease in males and females

By J. Nahar, Tasadduq Imam, K. Tickle, Yi-Ping Phoebe Chen. Expert systems with applications, 2013

412 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Information Management, Information Systems

View Paper: https://www.semanticscholar.org/paper/0e90cb3982299ee5e20121859646a251180d093f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Gautam Srivastava
2. Sonali Agarwal
3. Senthilkumar Mohan
4. Divya Tomar
5. Chandrasegar Thirumalai

In Health Information Management

1. Gautam Srivastava
2. Sonali Agarwal
3. Senthilkumar Mohan
4. Divya Tomar
5. Chandrasegar Thirumalai

In Information Systems

1. Gautam Srivastava
2. Sonali Agarwal
3. Senthilkumar Mohan
4. Divya Tomar
5. Chandrasegar Thirumalai

Citations in the corpus

• Effective Heart Disease Prediction Using Hybrid Machine Learning Techniques (2019, background): “CNN is able to generate features with various positions in the testing phase of the patient [22], [41].”
• A survey on Data Mining approaches for Healthcare (2013, methodology): “Rules Generation using Apriori for Healthy and Sick People [88]”