The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.
Zsombor ZrubkaGábor KertészLászló GulácsiJános CzereÁron HölgyesiHossein Motahari NezhadAbdolhossein Hemmati-SarapardehLevente KovacsAtul Janardhan ButteMárta PéntekPublished in: Journal of medical Internet research (2024)
The reporting quality of ML studies in the pediatric population with DM was generally low. Important details for clinicians, such as patient characteristics; comparison with the state-of-the-art solution; and model examination for valid, unbiased, and robust results, were often the weak points of reporting. To assess their clinical utility, the reporting standards of ML studies must evolve, and algorithms for this challenging population must become more transparent and replicable.