• MAMTA PATEL
• KINJAL THAKAR

Text mining technology is widely applied to a various fields. Semantic web, Information retrieval, Natural language processing and Machine learning text mining are influential areas in text mining. Multi-label learning has obtained important attention in the research area from previous few years. Medical data mining has large prospective for exploring the unrevealed patterns in the data sets of the medical field. Medical diagnosis plays significant role but still complex task that needs to be performed precisely and effectively. Applying automation of this system will be beneficial in medical science. Mining medical records for relationships between alive elements and the symptoms of a disease is an significant task. In this paper, we modify algorithm for mining medical terms having multi-label. This Research Paper leads to Decision Support System, Improved Health, Personalized Medicine and etc.

Machine Learning, NLP, LDA, Hybrid Classifier.

"Modified Algorithm For Mining Medical Terms Having Multi-Label Using Hybrid Classifier ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.330-336, April-2019, Available :http://www.jetir.org/papers/JETIR1904851.pdf

"Modified Algorithm For Mining Medical Terms Having Multi-Label Using Hybrid Classifier ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp330-336, April-2019, Available at : http://www.jetir.org/papers/JETIR1904851.pdf