In this era of information technology everyone needs information at the fingertip. With the development of IT various applications are developed in the medical field. This will make revolution in the medical field. Also, it will help doctors to know the recent developments and research carried out in the world. This will update the information of each and every doctor using such applications. Engineers are designing and developing best MEDLINE applications which are beneficial not only to doctors but also to the common peoples. All applications are user friendly. This will strengthen the present healthcare system. This paper introduces novel approach for identification and classification of disease and its treatment. We have also discusses all possible identification and classification approaches in this paper. The proposed approach uses the MEDLINE literature to extract all important biomedical information related to the respective disease and finding its treatment. Natural language processing (NLP) and data mining techniques are used to automatically extract information from MEDLINE literature. A software system automatically identi?es disease related terms from the MEDLINE abstracts.

1. Won Kim and Lana Yeganova," Identifying well-formed biomedical phrases in MEDLINE text", Journal of Biomedical Informatics, pp. 1035–1041, 2012.
2. Vikas Chaurasia and Saurabh Pal," Data Mining Approach to Detect Heart Dieses", International Journal of Advanced Computer Science and Information Technology (IJACSIT), Vol. 2, No. 4, pp. 56-66, 2013.
3. C. B. Sivaparthipan and V. Dheepa," Neural Network Based Online Learning and Identifying Disease-Treatment", International Conference on Computer Science and Information Technology (ICCSIT'2011), Dec. 2011
4. T. Sakthimurugan1 and S. Poonkuzhali", An Effective Retrieval of Medical Records using Data Mining Techniques", International Journal of Pharmaceutical science and Health,2012
5. O. Frunza, D. Inkpen and T. Tran, "A Machine Learning Approach for Identifying Disease Treatment Relations in Short Texts", IEEE Transactions on Knowledge and Data Engineering, Vol. 23, No. 6, June 2011
6. Rosario and Hearst, "Machine Learning (ML) Approach for Identifying Disease -Treatment Relations in Short Texts", IEEE Transactions on Knowledge and Data Engineering, 2011

Medline Application Biomedical Information Heath Care System