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. Here, MECP2 is linked to Rett syndrome.