Investigators from Monash University in Australia determined the prevalence of undiagnosed T2D to be 5.26% when utilizing machine learning to analyze modifiable markers not included in current screening guidelines. This equates to up to 29 million people worldwide with undiagnosed T2D by the year 2030. The research team compiled 16,429 medical files and stratified them based on the confirmation of undiagnosed T2D. They identified patients who lacked a current diagnosis and had a positive glycemic response to 1 of 3 tests. Three machine learning algorithms analyzed this group against 114 potential nutritional markers with 13 behavioral and 12 socio-economic variables. Investigators found significant anthropometric markers that included upper leg length, age at heaviest weight, waist circumference, and arm circumference.