DocumentCode :
3254957
Title :
Data mining in medicine: Current issues and future trends
Author :
Bhavya ; Mahak ; Mittal, Pooja
Author_Institution :
Dept. of CS & Applic., Maharshi Dayanand Univ., Rohtak, India
fYear :
2015
fDate :
19-20 March 2015
Firstpage :
979
Lastpage :
983
Abstract :
Unique Data mining is the methodology of investigating sets of information and afterward removing the significant information or learning. It is a term equivalent word with learning revelation. The materiality of this survey paper is highlighted by the way that the information mining is an object of exploration in numerous zones. In this paper, past works in range of information disclosure from therapeutic information are checked on. The objective to study this paper is to enhance proficiency, diminish human slip and help therapeutic specialists with enhanced learning. Medicinal information mining is extricating imaginative learning from the restorative information to enhance the proficiency, abatement cost and time and develop choice emotionally supportive network with objective of wellbeing advancement. We have considered papers from 1999 to 2013 with the plan to find learning from restorative information. A sum of six medicinal undertakings: screening, analysis, treatment, forecast, observing and administration are premise for investigation of each one paper and in each one assignment; we considered five information mining methodologies: order, relapse, bunching, affiliation and half and half. For each one assignment, outline and examination are expressed. The current issues and future slants are said. We hope this paper will further help to find new intriguing milestones for future examination.
Keywords :
data mining; learning (artificial intelligence); medical information systems; medicine; data mining; imaginative learning; information disclosure; medicinal information mining; medicine; restorative information; therapeutic information; therapeutic specialists; Computers; Data mining; Databases; Diseases; Medical diagnostic imaging; Standards; Association and Hybrid; Classification; Clustering; Data mining medicinal application; Knowledge disclosure; Medical information mining; Regression;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering and Applications (ICACEA), 2015 International Conference on Advances in
Conference_Location :
Ghaziabad
Type :
conf
DOI :
10.1109/ICACEA.2015.7164848
Filename :
7164848
Link To Document :
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