Heart Disease Prediction Using Ensemble Tree Algorithms: A Supervised Learning Perspective
Heart disease stands as a leading cause of morbidity and mortality globally, presenting a significant public health challenge. Therefore, early prediction and detection are critical, leading to timely and appropriate interventions at early stages. Four ensemble tree-based algorithms were used in thi...
Saved in:
| Main Authors: | Enoch Sakyi-Yeboah, Edmund Fosu Agyemang, Vincent Agbenyeavu, Akua Osei-Nkwantabisa, Priscilla Kissi-Appiah, Lateef Moshood, Lawrence Agbota, Ezekiel N. N. Nortey |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
|
| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/acis/1989813 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Anomaly detection using unsupervised machine learning algorithms: A simulation study
by: Edmund Fosu Agyemang
Published: (2024-12-01) -
A supervised machine learning statistical design of experiment approach to modeling the barriers to effective snakebite treatment in Ghana.
by: Eric Nyarko, et al.
Published: (2024-12-01) -
Advanced breeding strategies for combating rice salinity stress in Ghana: A critical review and future perspective
by: Mavis Owusuaa Osei-Wusu, et al.
Published: (2025-09-01) -
Using best-worst scaling experiment to understand factors influencing self-medication practices with antimicrobial drugs: A survey of students studying health programs at a tertiary institution in Ghana
by: Eric Nyarko, et al.
Published: (2025-01-01) -
Using best-worst scaling experiment to understand factors influencing self-medication practices with antimicrobial drugs: A survey of students studying health programs at a tertiary institution in Ghana.
by: Eric Nyarko, et al.
Published: (2025-01-01)