Melih Ağraz Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

Assistant Professor

John Brown University

faculty

6 h-index 25 pubs 75 cited

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Biography and Research Information

OverviewAI-generated summary

Melih Ağraz, an Assistant Professor at John Brown University, applies artificial intelligence to challenges in healthcare and computational biology. His research encompasses gene regulatory network analysis, cancer classification via gene expression patterns, and bioinformatics approaches to genomic networks. Ağraz also explores computational drug discovery methods. Recent work includes developing a machine learning pipeline (ML-GAP) that leverages autoencoders and data augmentation for improved genomic analysis. He also created a web tool (CERA) to optimize cutoff points in biomarker analysis. Ağraz's investigations extend to disease classification, such as thyroid disease, using generative adversarial networks, and enhancing predictions of severe hypoglycemia in type 2 diabetes with machine learning. His current research is centered on leveraging AI for improved disease understanding and treatment strategies.

Metrics

  • h-index: 6
  • Publications: 25
  • Citations: 75

Selected Publications

  • Enhanced Diabetes Prediction Using Novel Additive-Multiplicative Neural Networks: A Comprehensive Machine Learning Analysis of the PIMA Indians Dataset (2025) DOI
  • Semi-Supervised Machine Learning Approaches for Thyroid Disease Prediction and its Integration With the Internet of Everything. (2024) DOI
  • Gene Expression Assay: A New Panel for Early Metastatic Risk Estimation for Breast Cancer (2021) DOI

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