Ezhil Grace

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Publications (18)

• Integrating Statistical and Machine Learning Techniques to Analyze Expression Quantitative Trait Loci in Rheumatoid Arthritis
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-981-96-7753-5_25
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• Hybrid Meta Ensemble Framework for Oral Tissue Phenotype Classification Using Multispectral Imaging and Advanced Machine Learning
  National Academy Science Letters 2026 DOI: 10.1007/s40009-026-02421-2
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• Machine Learning-Enabled Rheumatoid Arthritis Classification Using GWAS Data: A Performance Analysis
  National Academy Science Letters 2025 DOI: 10.1007/s40009-025-01826-9
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• A Multidimensional Exploration of Hidden Burden of Rheumatoid Arthritis from Joints to Genes
  2025 DOI: 10.1007/978-981-96-3725-6_1
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• Composite SHAP Methylation Machine Learning Framework for Epigenetic Gene Ranking in Rheumatoid Arthritis
  Proceedings of 3rd International Conference on Intelligent Cyber Physical Systems and Internet of Things Icoici 2025 2025 DOI: 10.1109/ICoICI65217.2025.11252612
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• Optimized SNP Selection for Rheumatoid Arthritis Using Genetic Algorithm and Arithmetic Optimization Algorithm
  Proceedings 1st International Conference on Frontier Technologies and Solutions Icfts 2025 2025 DOI: 10.1109/ICFTS62006.2025.11031504
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• Pathway-Based Gene Prioritization and Machine Learning Approaches for Rheumatoid Arthritis Analysis
  Proceedings 1st International Conference on Frontier Technologies and Solutions Icfts 2025 2025 DOI: 10.1109/ICFTS62006.2025.11032011
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• Analysis and detection of DoS attacks using J48 algorithm compared with logistic regression algorithm to improve the detection rate
  Aip Conference Proceedings 2024 DOI: 10.1063/5.0232600
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• Spectrum sensing using entropy detection and comparing with Rayleigh fading test to improve the probability of detection
  Aip Conference Proceedings 2024 DOI: 10.1063/5.0228067
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• Comparative Analysis of Machine Learning Classifiers for Differentially Methylated Gene Classification in Rheumatoid Arthritis
  Learning and Analytics in Intelligent Systems 2024 DOI: 10.1007/978-3-031-65392-6_16
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