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Risk Prediction of Maternal Health by Model Analysis Using Artificial Intelligence

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Artificial Intelligence for Sustainable Development

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

Medical practice is being gradually transformed by artificial intelligence (AI). Diabetes mellitus (DM) is a disease characterized by inadequate control of blood glucose levels, and has the potential to create a healthcare crisis worldwide. Pregnant women who have gestational diabetes mellitus (GDM) may put their unborn children at risk. This form of diabetes can result in larger-than-normal offspring, making vaginal birth more difficult. This chapter presents a case study that uses an analysis of different machine learning methods to suggest a machine learning model for the early detection of gestational diabetes mellitus and the probability that it would proceed to type 2 diabetes.

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Authors and Affiliations

  1. Centre for Future Networks and Digital Twin, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Anandakumar Haldorai

  2. Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu, India

    Babitha Lincy R, Suriya Murugan & Minu Balakrishnan

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  1. Anandakumar Haldorai
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  2. Babitha Lincy R
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  3. Suriya Murugan
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  4. Minu Balakrishnan
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Haldorai, A., R, B.L., Murugan, S., Balakrishnan, M. (2024). Risk Prediction of Maternal Health by Model Analysis Using Artificial Intelligence. In: Artificial Intelligence for Sustainable Development. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-53972-5_6

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  • DOI: https://doi.org/10.1007/978-3-031-53972-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-53971-8

  • Online ISBN: 978-3-031-53972-5

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