Named Entity Recognition (NER) is a key task in Natural Language Processing (NLP). In medical domain, NER is very important phase in all end-to-end systems. In this paper, we investigate the performance of NER for disease (D-NER). TaggerOne was evaluated on 52 cardiovascular-related clinical case reports against hand annotation for diseases. Different training sets have been used to evaluate the performance of TaggerOne as a famous tool for NER in biomedical domain.