Adaptive Weighted Diversity Ensemble Learning Approach for Fetal Health Classification on Cardiotocography Data

Adaptive Weighted Diversity Ensemble Learning Approach for Fetal Health Classification on Cardiotocography Data

Accurate classification of cardiotocography (CTG) data is crucial for monitoring fetal health during pregnancy. However, existing methodologies face challenges in achieving precise classifications. This research aims to enhance fetal health assessment accuracy by developing a robust model through th...

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Bibliographic Details
Main Authors: K. Aditya Shastry, Mohan Sellappa Gounder, T. G. Mohan Kumar, D. U. Karthik, V. Sushma, D. Subashree
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Adaptive ensemble learning model
adaptive weighting
cardiotocography data analysis
diversity computation
fetal health classification
machine learning
Online Access:https://ieeexplore.ieee.org/document/10798107/
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