Data-Driven Strategies for Carbimazole Titration: Exploring Machine Learning Solutions in Hyperthyroidism Control.

Journal: The Journal of clinical endocrinology and metabolism
PMID: 39271154

Abstract

BACKGROUND: University Hospitals Dorset (UHD) has more than 1000 thyroid patient contacts annually. These are primarily patients with autoimmune hyperthyroidism treated with carbimazole titration. Dose adjustments are made by a healthcare professional (HCP) based on the results of thyroid function tests, who then prescribes a dose and communicates this to the patient via letter. This is time consuming and introduces treatment delays. This study aimed to replace some time-intensive manual dose adjustments with a machine learning model to determine carbimazole dosing. This can in the future serve patients with rapid and safe dose determination and ease the pressures on HCPs.

Authors

  • Thilo Reich
    Department of Computing & Informatics, Bournemouth University, Talbot Campus, Poole BH12 5BB, UK.
  • Rashid Bakirov
    Department of Computing & Informatics, Bournemouth University, Talbot Campus, Poole BH12 5BB, UK.
  • Dominika Budka
    Department of Computing & Informatics, Bournemouth University, Talbot Campus, Poole BH12 5BB, UK.
  • Derek Kelly
    Innovation Department, Poole Hospital, Poole BH15 2JB, UK.
  • James Smith
    Kangaroo Island Landscape Board, Kingscote, SA, 5223, Australia. james.smith@bushheritage.org.au.
  • Tristan Richardson
    Department of Medical Science & Public Health, Bournemouth University, Poole BH12 5BB, UK.
  • Marcin Budka
    Department of Computing and Informatics, Bournemouth University, Poole, United Kingdom.

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