Summary of Fuzzy Rule Based Intelligent Cardiovascular Disease Prediction Using Complex Event Processing, by Shashi Shekhar Kumar et al.
Fuzzy Rule based Intelligent Cardiovascular Disease Prediction using Complex Event Processing
by Shashi Shekhar Kumar, Anurag Harsh, Ritesh Chandra, Sonali Agarwal
First submitted to arxiv on: 19 Sep 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel intelligent system for cardiovascular disease (CVD) patients is proposed, leveraging Complex Event Processing (CEP) to analyze health parameters in real-time. The system uses fuzzy rule-based monitoring of clinical data to provide decision support, integrating Apache Kafka and Spark for data streaming, and Siddhi CEP engine for event processing. The approach categorizes synthetic data into risk categories, with validation results showing accurate predictions. This work aims to reduce the global burden of CVDs by providing timely and accurate disease prediction. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new system helps doctors make better decisions about heart disease patients. It uses special rules to analyze medical data in real-time, helping patients get the right treatment quickly. The system is tested with fake data and shows it can accurately predict how likely a patient is to develop heart disease. This could help save lives by giving doctors earlier warning signs of potential problems. |
Keywords
» Artificial intelligence » Synthetic data
