Transfer learning can help improve learning in medical tasks by using knowledge from different domains. A new algorithm called MS-TGHRR combines existing models with inductive knowledge from multiple domains to enhance classification accuracy on medical datasets. The experiments show that MS-TGHRR outperforms other multiple source transfer learning algorithms in classifying medical data.