Optimizing Healthcare Decisions: Evolving Big Data Into Smart Data to Analyze and Predict Medical Trends In Relation to Chronic Disease

Abstract

In the medical field, collection of big data is vital in understanding how to maintain a healthy general population. However, collection of big data alone is not robust enough to properly analyze trends. Big data, essentially, is just what the name suggests – a large set of information that may be observed for learning; however, big data is often not as structured as analysts would like it to be. Smart data is a much more polished version of big data, allowing for much more vigorous examination of trends and, more usefully, forecasting of what is to come. Thus, it is in the best of interest to evolve big data into smart data by a filtration process in which the garnered information is purified and organized in such a way that it may be deciphered and utilized effectively. With relation to healthcare, this level of insight is invaluable with regard to treating and preventing illness and disease. Appropriate health regulations, such as mandatory vaccinations, may be put in place as a result of these findings. Throughout this paper, various examples of data, in relation to lung cancer, melanoma, breast cancer, prostate cancer, and colon cancer will be collected and manipulated into smart data to produce more serviceable sets of information. In turn, projections of health trends may be created and decisions to benefit the affected may be made.