Developing a Model to Enhance the Quality of Health Informatics using Big Data
Praveen Kumar Sadineni
Abstract
Data world which is ruling us today not only established its identity in the field of computer science but also other interdisciplinary sectors such as healthcare, economics, media and communication etc. The speed and the size at which data is being produced by various applications led to the concept of Big Data which has transformed conventional data world to Digital data world. Big Data Analytics is an advanced technique which helps in analyzing large, distinct datasets which comprise structured, unstructured and semi-structured data of different sizes collected from several sources to find out unseen patterns, associations and other intuitions. Its applications are not only limited to banking, communiqué, social media, education, social services, trade and shipping but also extended to healthcare sectors. It provides healthcare services such as patients prediction to expand staff employment, Electronic Health Records (EHRs), Telemedicine etc. This paper elaborates on how machine learning techniques such as Decision Trees, Support Vector Machine (SVM) and K nearest Neighbor can be integrated with Big Data Analytics to enhance the quality of healthcare services such as Heart Disease examination. Performance comparison of the techniques is evaluated using metrics such as Accuracy, Recall and Specificity.