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OntoMG: a unique and ontological-based intelligent framework for early identification of myasthenia gravis (MG)

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Abstract

Myasthenia Gravis (MG) is a neuromuscular disease causing extreme muscular fatigue, triggering problems with vision, swallowing, speech, mobility, dexterity, and breathing. However, early detection and prediction of MG is a crucial and quite challenging task for medical practitioners. So, in our proposed work, we are focused on introducing an ontology-based intelligent system for the prognosis of patients affected by this neuromuscular disease. The given paper presents a novel framework that employs the concepts of ontology, semantic web rules, and reasoner for deriving whether the patient is tested positive or negative. The suggested framework's effectiveness is assessed by comparing it to machine learning classifiers using parameters from the NIH repository for Myasthenia Gravis. The experimental results show that the ontological-based framework is able to achieve higher accuracy (80.85%), higher precision (78.37%), and higher recall (76.55%) than the existing classifiers used in the recent studies.

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Funding

The writers have not received any financial support from the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Computer Science and Information Technology, Jain (Deemed to Be University), Bengaluru, India

    Prerna Mahajan

  2. Maharishi School of Engineering and Technology, Maharishi University of Information Technology, Lucknow, India

    Trapty Agarwal

  3. Department of Computer Science and Engineering, Faculty of Engineering and Technology, Parul University, Vadodara, Gujarat, India

    Daxa Vekariya

  4. Department of Management, Sanskriti University, Mathura, UP, India

    Rajesh Gupta

  5. Department of UGDX, ATLAS SkillTech University, Mumbai, India

    Ashwini Malviya

  6. Department of Computer Science Engineering, Presidency University, Bengaluru, India

    S. P. Anandaraj

  7. Department of Computer Science and Business Systems (CBS), Noida Institute of Engineering and Technology, Greater Noida, Uttar Pradesh, India

    Garima Jain

  8. Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh, India

    D. Anand

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  1. Prerna Mahajan
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  2. Trapty Agarwal
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  3. Daxa Vekariya
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  4. Rajesh Gupta
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  6. S. P. Anandaraj
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  7. Garima Jain
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Correspondence to Prerna Mahajan.

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Mahajan, P., Agarwal, T., Vekariya, D. et al. OntoMG: a unique and ontological-based intelligent framework for early identification of myasthenia gravis (MG). Int. j. inf. tecnol. (2024). https://doi.org/10.1007/s41870-024-01908-9

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  • DOI: https://doi.org/10.1007/s41870-024-01908-9

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