Improved Inception-Capsule deep learning model with enhanced feature selection for early prediction of heart disease.

ABSTRACT: Heart disease continues to rank among the world's top causes of death, underscoring the pressing need for precise and accurate prediction techniques. Performance issues with traditional machine learning techniques have been identified, particularly when working with high-dimensional and unbalanced medical datasets. We present a new deep learning-based framework called IDLHICNet, or an Improved Deep Learning-based Hybrid Inception-Capsule Network, which is combined with an Enhanced Whale Optimization Algorithm (EWOA) for feature selection in order to overcome this issue. Using Improved K-Means Clustering (IKC) to remove outliers, Min-Max normalization to scale features, SMOTE oversampling to balance classes, and EWOA to select essential features are some of the crucial steps in the proposed

SUBMITTER: Nayak MSS 

PROVIDER: S-EPMC12464333 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature