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Artificial Intelligence and Machine Learning Techniques in the Diagnosis of Type I Diabetes: Case Studies

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Artificial Intelligence and Autoimmune Diseases

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1133))

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Abstract

The US Food and Drug Administration (FDA) approved the first AI-based medical device in 2012. Recently, there has been a notable surge in AI-based devices for diagnosing and managing diabetes. Although several AI-related devices are prevalent in diagnostic imaging and analysis, AI-driven devices for diabetes care are not yet widely available globally. AI technology is being explored in various aspects of diabetes management, encompassing self-management tools, automated retinal screening, clinical diagnosis aids, and risk assessment and categorization. Moreover, several studies have delved into utilizing AI for predicting diabetes, while there has been significant research into refining insulin dosage control. A noteworthy advancement includes AI systems alerting diabetic patients in advance about potential hypoglycemic attacks, marking a considerable stride in diabetes care innovations. This chapter discusses the application of AI and machine learning techniques in diagnosing Type I Diabetes, offering insights through case studies.

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Authors and Affiliations

  1. Advanced Structures and Composites Center, University of Maine, 177 Aubert Hall, Orono, ME, 04469, USA

    Ahmad A. L. Ahmad

  2. Department of Chemistry, University of Sharjah, Sharjah, 27272, UAE

    Ahmed A. Mohamed

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  1. Ahmad A. L. Ahmad
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Correspondence to Ahmed A. Mohamed .

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Editors and Affiliations

  1. Department of Computer Science, Jamia Millia Islamia, New Delhi, Delhi, India

    Khalid Raza

  2. Department of Pharmacology, All India Institute of Medical Sciences, New Delhi, Delhi, India

    Surender Singh

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Ahmad, A.A.L., Mohamed, A.A. (2024). Artificial Intelligence and Machine Learning Techniques in the Diagnosis of Type I Diabetes: Case Studies. In: Raza, K., Singh, S. (eds) Artificial Intelligence and Autoimmune Diseases. Studies in Computational Intelligence, vol 1133. Springer, Singapore. https://doi.org/10.1007/978-981-99-9029-0_14

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