Techniques of Data Stream Mining for Health Care Application

Data stream mining plays a key role to analyze the continuousdata. The effective and efficient analysis of this data in suchdifferent forms becomes a challenging task. Developments insensors device, miniaturization of low power microelectronicsdevice, and wireless networks devices arebecoming a significant opportunity for good quality of healthcare services. Signals like ECG, EEG, and BP etc. can bemonitor through wireless sensor networks and analyzed withthe help of data mining techniques. These real-time signals arecontinuous in nature and abruptly changing hence there is aneed to apply an efficient and concept real-time data streammining techniques for taking intelligent health care decisions.The high speed and large amount of data set in data stream, thetraditional classifier and classification technologies are nomore applicable. The important criteria are to handle the‘concept drift’ in data streams mining. Data Stream Mining(DSM) process performs data analysis and may uncoverimportant data patterns, knowledge base data, and scientificand medical research data.