![]() ![]() We will also analyze and examine possible future work for each of these areas, as well as how combining data from each level may provide the most promising approach to gain the most knowledge in Health Informatics. ![]() In addition to gathering data at multiple levels, multiple levels of questions are addressed: human-scale biology, clinical-scale, and epidemic-scale. This paper will present recent research using Big Data tools and approaches for the analysis of Health Informatics data gathered at multiple levels, including the molecular, tissue, patient, and population levels. Big Data, Health Informatics, and the Future of Cardiovascular Medicine Authors: Joonseok Kim University of Alabama at Birmingham Citations 43 1,536 1 Learn more about stats on ResearchGate. The basic goal of Health Informatics is to take in real world medical data from all levels of human existence to help advance our understanding of medicine and medical practice. However, there are a number of issues that arise when dealing with these vast quantities of data, especially how to analyze this data in a reliable manner. ![]() With big data analytics, data scientists and others can analyze huge volumes of data that conventional analytics and business intelligence solutions cant touch. In addition, this information can improve the quality of healthcare offered to patients. Big data analytics is the process of examining big data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better decisions. The amount of data produced within Health Informatics has grown to be quite vast, and analysis of this Big Data grants potentially limitless possibilities for knowledge to be gained. ![]()
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