Sangeetha, T and Manikandan, K and Victor Arokia Doss, D (2024) Optimized Deep Learning Model for Early Cardiomyopathy Classification Using Microarray Gene Expression Data. Optimized Deep Learning Model for Early Cardiomyopathy Classification Using Microarray Gene Expression Data. pp. 1-9.

[thumbnail of Phase 4_Published_TSangeetha.pdf] Text
Phase 4_Published_TSangeetha.pdf - Published Version
Download (618kB)

Abstract

Background: Cardiomyopathy, a leading cause of chronic
heart failure, necessitates early diagnosis to improve
patient outcomes. Traditional diagnostic methods, both
manual and automated, often result in misclassification
and inaccurate detection. This study proposes an
optimized hyperparameter-tuned deep neural network
model, the Protein Synthesis Defined Deep Belief Network
(PSDBN), for accurate Cardiomyopathy classification
using gene expression data from microarrays. Methods:
The study involved preprocessing gene expression data to
address missing values through K-Nearest Neighbour
imputation, followed by dimensionality reduction using
Singular Value Decomposition. Feature extraction was
performed using Kernel Principal Component Analysis,
and Particle Swarm Optimization was employed for
feature selection. The selected features were fed into the
PSDBN, which was fine-tuned for optimal performance.
Results: The PSDBN model was evaluated on the
GSE138678 dataset from the GEO repository. Performance
metrics, including precision, recall, and F1-score, were
calculated using cross-validation. The PSDBN
outperformed traditional models, achieving a precision of

X%, recall of Y%, and F1-score of Z%, significantly
reducing overfitting and computational complexity.
Conclusion: The proposed PSDBN model, with its robust
preprocessing, feature extraction, and optimization
techniques, demonstrates superior accuracy in classifying
Cardiomyopathy types and predicting disease prognosis,
offering a promising tool for early diagnosis and improved
patient management.

Item Type: Article
Uncontrolled Keywords: Cardiomyopathy, Gene Expression, Deep Belief Network, Particle Swarm Optimization, Machine Learning
Divisions: PSG College of Arts and Science > Department of Computer Science
Depositing User: Mr Team Mosys
Date Deposited: 05 Oct 2024 05:36
Last Modified: 05 Oct 2024 05:36
URI: https://ir.psgcas.ac.in/id/eprint/2310

Actions (login required)

View Item
View Item