Diabetes mellitus is a common medical condition now considered a major public health challenge. Developing new tools for patient management is essential to increase their quality of life. This episode presents how artificial intelligence can be applied to the treatment of diabetes, particularly in the prediction of the presence of pain in patients with diabetic peripheral neuropathy and in the detection of gestational diabetes.

REFERENCES

1. Tomic D, Shaw JE, Magliano DJ. The burden and risks of emerging complications of diabetes mellitus. Nat Rev Endocrinol. 2022. Available at: https://doi.org/10.1038/s41574-022-00690-7
2. Baskozos G, Themistocleous AC, Hebert L, Pascal MMV, John J, Callaghan BC, et al. Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts. BMC Med Inform Decis Mak. 2022;22:144. Available at: https://doi.org/10.1186/s12911-022-01890-x
3. Du Y, Rafferty AR, McAuliffe FM, Wei L, Mooney C. An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus. Sci Rep. 2022;12:1170. Available at: https://doi.org/10.1038/s41598-022-05112-2

NON-2023-3518