Extended Data Fig. 1: Performance improvement of double syndromes and double subjects when using different base sample sizes with Face2Gene models and the Face2Gene rare set.
From: GestaltMatcher facilitates rare disease matching using facial phenotype descriptors
Base sample size is calculated as the number of subjects multiplied by the number of syndromes. For example, the point of 40 subjects and 10 syndromes has sample size of 400, and it equals both the point of 10 subjects and 40 syndromes and the point of 20 subjects and 20 syndromes. ΔTop-10 accuracy is the difference of accuracy between the double syndromes or subjects and the base point, and is calculated based on Fig. 3. Take the two points annotated in the figure as two examples. The base point is 10 subjects and 40 syndromes with sample size 400. The upper indicated point is subtracting the point of 10 subjects and 40 syndromes from the point of 10 subjects and 80 syndromes in Fig. 3. The lower point is subtracting the point of 10 subjects and 40 syndromes from the point of 20 subjects and 40 syndromes in Fig. 3. In this graph, doubling the number of syndromes always improves top-10 accuracy more than doubling the number of subjects, particularly at larger base sample sizes. Thus, adding more syndromes is more effective than adding more subjects when enlarging the training set.
