M-polynomial driven machine learning models for predicting physicochemical properties of antibiotics

• Xin Li ,

  Contributed equally to this work with: Xin Li, Masoud Ghods, Negar Kheirkhahan

  Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Department of Gynecology, Renmin Hospital of Wuhan University, Wuhan, China

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• Masoud Ghods ,

  Contributed equally to this work with: Xin Li, Masoud Ghods, Negar Kheirkhahan

  Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  * E-mail: mghods@semnan.ac.ir

  Affiliation Department of Applied Mathematics, Semnan University, Semnan-19111, Iran

  https://orcid.org/0000-0002-5006-5107

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• Negar Kheirkhahan ,

  Contributed equally to this work with: Xin Li, Masoud Ghods, Negar Kheirkhahan

  Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Department of Applied Mathematics, Semnan University, Semnan-19111, Iran

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• Jana Shafi

  Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

  Affiliation Department of Computer Engineering and Information, College of Engineering in Wadi Alddawasir, Prince Sattam Bin Abdulaziz University, Wadi Alddawasir, Saudi Arabia

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