Although it falls within the realm of science, the connection between this grand challenge and computer science is less obvious than with the natural sciences. There are many ways in which computer science may be used to improve nutrition to fight obesity.
One of them involves the ability of computers to perform mass calculations at inhumanly fast rates. Using pre-existing algorithms, or sets of instructions, a computer program can take a large collection of data and analyze various attributes to produce predictions and statistics much more quickly and potentially accurate than humans can do by hand. Data mining is defined as the search for patterns within large sets of data. For example, computers can take in a large number of patient records and return a series of trends or calculations quickly and accurately. The figure to the left depicts a table containing data on space shuttle attributes. Data mining for our grand challenge specifically would probably involve attributes for medical traits such as smoking habits, family history, demographics, and various systematically collected health levels. Even given the obvious sensitivity of medical data, we have access to thousands upon thousands of patient records over the past decades that can be applied to modern-day problems by looking at the trends they convey.
Another application of computer science uses the newly emerging industry of wearable technology. In recent years, major corporations in the technology field such as Samsung and Apple have established themselves in the wearable technology market. Due to the short time it has been available to the public, there is still a decent amount of untapped potential in the ability of this technology to aid in problems of disease and obesity in America. For instance, applications on these devices could potentially provide instant feedback to the user on their present internal health status in unprecedented ways. They are currently used for mostly physical characteristics collected digitally by hardware within the watches and bands such as walking distance, calories burned and stairs climbed. The devices have a lot of potential to be used for extensive health monitoring on an individualized basis but application developers have not yet embraced the challenge to use the tools given by the devices themselves to design an interface that brings medical information to the individual wearer.
The field of computer science encompasses multiple platforms of applications, including mobile and web. The progress of these applications demonstrated since their inception has been impressive to say the least. For every idea someone has, it is likely there is already a mobile and/or web application for it on the market. Despite this, the ability of applications to convey personalized information and feedback is highly undervalued. In addition, the extent to which these applications appear in our daily lives can be used to the advantage of the solution to our grand challenge. Technology is a way to communicate our message quickly, effectively and consistently. If our solution involves improving communication between scientists and the general public, the implementation is best resolved using some technological platform that is easily accessible and geared towards the intended audiences, something that is relatively easy to do given our current technological progress.