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A Review of Data-Driven Liver Disease Risk Prediction through Machine Learning Algorithms
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 185 - Number 33 |
| Year of Publication: 2023 |
| Authors: Riya, Barinderjit Kaur |
10.5120/ijca2023922960
|
Riya, Barinderjit Kaur . A Review of Data-Driven Liver Disease Risk Prediction through Machine Learning Algorithms. International Journal of Computer Applications. 185, 33 ( Sep 2023), 6-8. DOI=10.5120/ijca2023922960
Abstract
Millions of individuals throughout the world suffer from liver disease, which is a major health issue. Early diagnosis and treatment of liver illness can significantly enhance health outcomes and lower medical expenses. Healthcare providers in underdeveloped nations might find this strategy very helpful. A hybrid technique has been introduced to accurately diagnose liver disease. Scalability and prediction have been computed. A new patient's data was used as input, and it was discovered that the model produced good accuracy for detecting livers. In the final section of this work, we conclude that the hybrid strategy is preferable after thoroughly analyzing the available data.
References
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- Stage of liver disease collected from dreamstime.com.
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