A mono-quantitative research choice will be involved in this current study to develop a discussion on the impacts of AI algorithms and ML in order to minimise diagnostic errors within young diabetic patients. In this account, Ojebode et al. (2018), highlighted that the choice of a mono-quantitative research method delivers a focused-based approach along with a consistent effort to analyse for comprehensive investigation via accurate information, single data collection method, and quantitative data collection techniques. In such a context, quantitative research will be better to conduct a systematic collection and examination of statistical data, therefore, it will contribute in quantification of different variables concerning the young diabetic patients along with diagnostic errors in their diabetic treatment in the healthcare sector of the UK. Mono-qualitative research choice will not be taken in this research as this kind of research lacks statistical data, requiring evaluation of the effectiveness of AI and ML tools in order to reduce diagnosis errors. Therefore, it would be beneficial for this current study to opt for mono-quantitative research in order to offer comprehensive insights regarding the use of AI and ML to reduce diagnosis errors in the UK healthcare sector for young diabetic patients.