Risk prediction of cardiovascular disease using machine learning classifiers
importance 8/10
ai assisted
Artificial Intelligence in Healthcare cardiovascular diagnostics stage: research
Problem
Early, automatic detection of cardiovascular disease to prevent death or physical paralysis.
Why it matters
Cardiovascular disease often leads to death; early detection can save lives.
What the AI did
Trained multi-layer perceptron and K-nearest neighbour classifiers on public UCI data, after removing outliers and null-valued attributes, to detect cardiovascular disease.
Results
82.47% accuracy and 86.41% AUC using the MLP model.
Impact
Moderate detection accuracy on a public dataset; clinical deployment not stated.
Record
| Venue | Open Medicine |
|---|---|
| Published | 2022 |
| Work type | article |
| Authors | Madhumita Pal, Smita Parija, Ganapati Panda, Kuldeep Dhama, Ranjan K. Mohapatra |
| Citations | 158 (OpenAlex, at import time) |
| References | 23 |
| Model or method | Multi-layer perceptron (MLP); K-nearest neighbour (K-NN) |
| Organization | not stated in source |
| Primary source | https://doi.org/10.1515/med-2022-0508 |
| Open access | gold |
| Keywords | cardiovascular disease, machine learning, MLP, K-NN, classification |
Importance rating
8
major — millions of lives, an industry or a field
Abstract states CVD often leads to death or physical paralysis and early detection can save many human lives; a major disease, though no scale numbers given.