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AI and ML for Reducing Diagnostic Errors in Young Diabetic Patients

Analysis of AI and Machine Learning tools in reducing diagnostic errors among young diabetic patients within the UK healthcare industry using a deductive approach.

Category: Health

Uploaded by Katherine Price on May 9, 2026

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The research is going to apply a deductive research approach as it begins with an analysis of effectiveness of AI along with Machine Learning that seems to reduce diagnostic errors occurring among young diabetic patients in the healthcare industry of the UK. In such a context, Casula et al. (2020) stated that one visible benefit of applying the deductive research approach which promotes the concepts along with variables drives cause-effect within the research.

The deductive approach assists in execution of formal inference guidance, resulting in a more accurate and precise deduction of an examination. In this lexicon, the deductive approach is going to assess the significance of AI and ML tools in overcoming diagnostic errors within young adults in the UK. On the contrary, the inductive research approach would not be involved due to its subjective norms and generalisations that are unable to be directly associated with the research objectives (Woiceshyn & Daellenbach, 2018). Hence, undertaking a deductive research approach can be effective for the current research to analyse the impact of AI and ML tools in minimising diagnostic errors within young diabetic patients in the UK.

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