All of society is subject to change, especially in our rapidly advancing age of technology. Every year new gadgets and inventions flood marketplaces, homes, schools, workplaces. Despite these advances in technology, the field of medicine is yet to experience such rapid advancements. However, the use of electronic health records (EHR) in hospitals is increasing rapidly, and hence an availability of large volumes of patient data and information about various treatments and diagnoses. Big Data provides the opportunity for the medical field to experience huge advancements and changes. IBM’s Watson is currently leading the way to this sort of change. In healthcare, most of the data available include personal medical records, radiology images, clinical trial data, FDA submissions, human genetics, population data and genomic sequences. In 2012, it was estimated that the volume of healthcare data was 500 petabytes and expected to grow in 2020 to 25,000 petabytes. This enormous amount and variety of ...
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... an effective way to integrate robotics with cognitive systems, but that’s another topic for later.
The practice of medicine is at a crossroads, with simultaneous increases in patient volume, an explosion in the amount and complexity of medical and scientific knowledge, and the transition to electronic medical records. A report on the nation’s cancer care system stated, the United States has an “increasingly chaotic and costly” medical system that is in crisis and fails to deliver consistent care that is evidence based, coordinated, and patient centered. The combination of AI, big data, and massively parallel computing offers the potential to create a revolutionary way of practicing evidence-based, cost-effective, and personalized medicine. However, barriers to adoption of AI technologies must be overcome from regulatory, legal, cultural, and political perspectives.
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