Evidence map›Paper›PMID 41028044›Full record

ArticleScientific reports2025

Prediction of suitable drug for keloid through analytic hierarchy process and topological indices.

K Janagi, A Usha, Rashad Ismail, M C Shanmukha

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

K JanagiDepartment of Pure and Applied Mathematics, Alliance University Alliance College of Engineering and Design, Bengaluru, 562106, India.
A UshaDepartment of Pure and Applied Mathematics, Alliance University Alliance College of Engineering and Design, Bengaluru, 562106, India.
Rashad IsmailDepartment of Mathematics, Faculty of Science and Arts, King Khalid University, 61913, Abha, Mahayl Assir, Saudi Arabia. rismail@kku.edu.sa.
M C ShanmukhaDepartment of Mathematics, PES Institute of Technology and Management, Shivamogga, 577204, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the study is to identify the most suitable drug in treating Keloid, from the considered drugs using Multi Criteria Decision Making (MCDM) technique, Analytic Hierarchy Process (AHP) via degree-based topological indices. Topological indices play a vital role in predicting the biological and physicochemical properties of chemical compounds by deriving them from the molecular structure using specific rules. Given the growing prevalence of keloid cases, there is an increasing need for safer and more effective drugs. This study investigates 12 keloid drugs by applying the QSPR technique with respect to their physicochemical properties. The drugs are ranked using the AHP with specific criteria, allowing for the identification of the most effective drug combinations to help in the development of improved treatments for keloids. From the analysis, it is observed that the most effective and suitable drug is Doxorubicin while the least effective drug is 5-Fluorouracil.

Indexed as

KeloidDoxorubicinFluorouracilHumansDoxorubicinFluorouracilAHPComplexityKeloidMolecular weightNon-hydrogen atom count (heavy atom count)Topological indices

Identifiers

PMID41028044
PMCPMC12485030

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.