An interpretable and balanced machine learning framework for Parkinson’s disease prediction using feature engineering and explainable AI

• Nasim Mahmud Nayan,

  Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Writing – original draft

  Affiliation Department of Computer Science and Engineering, University of Information Technology and Sciences (UITS), Dhaka, Bangladesh

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• Al Mamun Rana,

  Roles Data curation, Project administration, Software, Supervision

  Affiliation Faculty of Fine Arts, Rajshahi University, Rajshahi, Bangladesh

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• Md. Monirul Islam,

  Roles Investigation, Methodology, Project administration, Validation, Writing – review & editing

  Affiliation Department of Information and Communications Engineering, Hankuk University of Foreign Studies, Seoul, South Korea

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• Jia Uddin,

  Roles Methodology, Resources, Software, Supervision, Writing – original draft

  Affiliation Artificial Intelligence and Big Data Department, Woosong University, Daejeon, Republic of Korea

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• Tahmina Yasmin,

  Roles Conceptualization, Investigation, Visualization, Writing – review & editing

  Affiliation School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom

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• Jasim Uddin

  Roles Funding acquisition, Resources, Supervision, Writing – original draft, Writing – review & editing

  * E-mail: juddin@cardiffmet.ac.uk

  Affiliation EM-RFMic Engineering Group, Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, United Kingdom

  https://orcid.org/0000-0002-0735-9038

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