Role of Artificial Intelligence in Thyroid Disorder

In clinical research, personalised medicine, and medical diagnostics, Artificial Intelligence (AI) is transforming healthcare and providing new tools. It is evident that using artificial intelligence technologies can help doctors and laboratory medicine professionals improve test prescription, test interpretation, decision-making, process optimization, and assay design. AI make use of mathematical models to carry out functions that need human like intellect. The diagnosis and risk assessment of thyroid disorders has both shown promise in the use of AI-based technologies. AI algorithms can provide more accurate and efficient assessments by considering multiple things into consideration at once by analysing a patient's medical history, symptoms, and laboratory results. This helps diagnose thyroid disorders very precisely. Thyroid disease, particularly hypothyroidism, affects people of all ages and is projected to continue to rise with increasing age. Because the Thyroid stimulating hormone (TSH) reference range must be adjusted for age, body fat and other characteristics such as multidrug therapy and overall well-being, clinical diagnosis of hypothyroidism is difficult. To treat hypothyroidism, someone needs vigilance, tackling cardiovascular disease, and tailored therapy. Therapies of subclinical hypothyroidism (SCH) in the old population must be done with caution, led by growing age, and the severity of SCH. TSH level of 10 m U/l appears to be the suitable beginning; however, it should be reconsidered on a frequent basis, and the Levothyroxine (LT4) dose should be adapted to the participant's well-being and the existence of dyslipidaemia and other metabolism abnormalities.