An expert system for diagnosing and treating heart disease
February 21, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Blake Fernandino, Moein Samak Bisheh
arXiv ID
2402.14128
Category
cs.HC: Human-Computer Interaction
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Timely detection of illnesses is vital to prevent severe infections and ensure effective treatment, as it's always better to prevent diseases than to cure them. Sadly, many patients remain undiagnosed until their conditions worsen, resulting in high death rates. Expert systems offer a solution by automating early-stage diagnoses using a fuzzy rule-based approach. Our study gathered data from various sources, including hospitals, to develop an expert system aimed at identifying early signs of diseases, particularly heart conditions. The diagnostic process involves collecting and processing test results using the expert system, which categorizes disease risks and aids physicians in treatment decisions. By incorporating expert systems into clinical practice, we can improve the accuracy of disease detection and address challenges in patient management, particularly in areas with limited medical resources.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted