Similarly, the appearance of key terms such as ‘MECP2’ for Rett syndrome (Fig. 3b, middle), ‘merlin’ for Meningioma (Fig. 3b, bottom), ‘sickle’ for Erythrocyte (Fig. 3a, middle), and ‘bronchoalveolar’ for Pulmonary acinus (Fig. 3a, bottom) demonstrate that our models successfully identify relevant features from the metadata text that significantly contribute to its the correct tissue and disease annotation predictions. This evidence concerns the gene MECP2 and meningioma.