Table 1. Training and Test Sets.

All included images from the North American, Nepali, and combined datasets were split such that 90% of the images were distributed into the training set (A) and 10% of the images were distributed into the test set (B). Each dataset was stratified to maintain similar ratios of images with and without stage in each training and test set, as well as separated on a patient-level to ensure all training and test sets contained no overlapping patients. Each training set (A) was further split into 5 cross validation splits, retaining the underlying distribution of stage. Models were created using the North American dataset alone, the Nepali dataset alone, or both datasets combined. A) Training Set, divided into 5 splits for 5-fold Cross Validation

	No. in Training Split						No. In Validation Split
	Total		North American Dataset		Nepali Dataset		Total		North American Dataset		Nepal Dataset
Splits	Images	Patients	No Stage	Stage	No Stage	Stage	Images	Patients	No Stage	Stage	No Stage	Stage
1	7899	895	3018	1102	3599	180	2138	231	735	380	995	28
2	7941	882	2901	1161	3694	185	2096	244	852	321	900	23
3	7977	899	2998	1191	3651	137	2060	227	755	291	943	71
4	8149	909	3056	1263	3661	169	1888	217	697	219	933	39
5	8033	893	2974	1145	3762	152	2004	233	779	337	832	56