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International Journal of Creative and Open Research in Engineering and Management

A Peer-Reviewed, Open-Access International Journal Supporting Multidisciplinary Research, Digital Publishing Standards, DOI Registration, and Academic Indexing.
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ISSN: 3108-1754 (Online)
Crossref DOI: Available
ISO Certification: 9001:2015
Publication Fee: 599/- INR
Compliance: UGC Journal Norms
License: CC BY 4.0
Peer Review: Double Blind
Volume 02, Issue 7

Published on: July 2026

TOPOLOGICAL ANALYSIS OF DIABETES MELLITUS DRUGS USING GRAPH THEORY, LINEAR REGRESSION MODELS, AND PREDICTIVE MACHINE LEARNING SUITES

Pavan K R K Abhishek

Post Graduation Department-Data Science, Jyothy Institute of Technology, Pipeline Rd,

Near Ravi Shankar Guruji Ashram, Tatguni, Bengaluru, Agara, Karnataka 560082, India

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Plagiarism Passed Peer Reviewed Open Access

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Abstract

This research article integrates molecular graph theory with computational data science techniques to analyze the physicochemical behavior of key therapeutic agents used in the management of Type II Diabetes Mellitus. Quantitative Structure-Property Relationship (QSPR) models are constructed utilizing our newly proposed Degree Logarithmic Fraction (DLF) index, mapped against four prominent antidiabetic drugs: Metformin, Nateglinide, Pioglitazone, and Dapagliflozin. We bridge standard graph theoretical derivations with localized machine learning regressors. The evaluations are conducted via strict localized training fits coupled with Leave-One-Out Cross-Validation (LOOCV) loops to gauge predictive stability over sparse molecular sample frameworks.

KEYWORDS: QSPR analysis, Linear Regression, XGBoost, Support Vector Regression, DLF index, Antidiabetic Drugs.

How to Cite this Paper

R, P. K. & Abhishek, K. (2026). Topological Analysis of Diabetes Mellitus Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(7), 1-9. https://doi.org/10.55041/ijcope.v2i7.180

R, Pavan, and K Abhishek. "Topological Analysis of Diabetes Mellitus Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijcope.v2i7.180.

R, Pavan, and K Abhishek. "Topological Analysis of Diabetes Mellitus Drugs Using Graph Theory, Linear Regression Models, and Predictive Machine Learning Suites." International Journal of Creative and Open Research in Engineering and Management 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijcope.v2i7.180.

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References

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  • All submissions are screened under plagiarism detection.
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  • Peer Review Type: Double-Blind Peer Review
  • Published on: Jul 18 2026
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