As the medical industry transitions into the era of big data, new technology is needed to process the enormous amounts of data the healthcare industry will be working with. By 2020, there will be 200 times more data than any physician can absorb.
The data for a single individual is 0.4 terabytes of medical records, 6 terabytes of genomic records and a startling 1,100 terabytes of exogenous data. This makes 1,106.4 terabytes of medical information per person. No hospital will be able to store and analyze that much data. A shared solution is required to handle all these personal health statistics.
Ideally, an artificial intelligence program is desired to connect doctors’ data to each other. An Intelligence-as-a-Service network can make it possible for doctors to tap into knowledge from specialists anywhere when they encounter a medical situation that is not responding to a treatment.
The Watson Health Cloud, a cognitive, open platform made to aggregate the advanced analytics that the next generation of big medical data will require, created by Robert Merkel, is possibly the solution to sorting and sharing data. Merkel’s program can possibly enable collective intelligence, taking patient data and applying evidence based insight in an outcome driving learning system. In this approach, data is used in a bio-intelligence framework, similar to deep learning. Multiple layers of analytics are used to extract value from the data.
The Watson Health Cloud, launched in the fall of 2014, is making it possible to receive a message from an artificial intelligence program based on your own medical data, instead of having to see a physician for a yearly or biyearly checkup. With this new technology, hospitals will be able to pull the data stored in the Watson Health Cloud from real-time information devices, other doctor’s notes and other clinical data to best care of their patients.
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