Healthcare Is Evolving And Applying New Innovations Into Its Field

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Healthcare is rapidly evolving and applying new innovations into its field. It now includes more concepts that combine both information and technology, for example, the area of health information technology (HIT). Health information technology is also known as health informatics and includes the different areas of clinical specialties or diseases, user, agent, technology, and information level (Martin-Sanchez, Maojo, & Lopez-Campos, 2002). The field of bioinformatics fits into the category of health information technology because it is a disciplinary field that involves both science/ health and technology (Hoyt, 2010). Bioinformatics is a field that combines, “computer science with biological and biomedical sciences such as…show more content…
The database must also be able to, “accept, store, and manage molecular physiology data” (Moore, 2007). In doing so, selecting the correct database is essential, and many companies choose to create their own private database. However, the creation and use of public databases are on the rise. After all the genetic information has been inputted into a database, it needs to be analyzed. Data analysis consists of data mining and machine learning methods, through the use of high-powered computers. Data analysis is also used for identifying any bimolecular patterns in the observed outcome (Moore, 2007). In addition, data mining is then used to manage and study the genetic information. After all of the analysis and studying, the interpretation of the information is what is most important. The researchers need to be able to understand and comprehend what the data information signifies. From there, bioinformatics can then be used for other various resources. For instance, bioinformatics can be valuable in delivering therapeutics (Bioinformatics, 2000). Bioinformatics is important because it allows researchers and scientists to study genetic information and to be able to add to the database(s). Furthermore, it led to the emergence of computational biology, in which researchers and scientists could interpret the genetic data (Hagen, 2000). Computational biology involves the use of, “algorithms and artificial intelligence to: find
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