What Does Synthetic Data Mean In Healthcare ’s Artificial Intelligence Revolution?

Data is the foundation of artificial intelligence. As the importance of A.I. grows in modern medicine, there’s a huge need for data (as well as data annotation) – the latter being one of the most important aspects of the work in building an algorithm. In healthcare, collecting data means utilising existing databases and using images, radiology results, samples, CT or MR scans, patient records and more. The more data you feed the system, the better the results can become.  Artificial intelligence has earned its place in multiple fields of medicine, from recognising patterns, supporting diagnoses and setting up treatment pathways to optimising healthcare logistics. Smart algorithms can sift through large volumes of data no man can, deriving clear-cut trends from such analyses.  It’s easy to guess that this data includes your own health-related data: EMRs, smartwatches, genetic reports, wearables and so on are all means to feed the A.I. with datasets. But what if we would never be able to obtain enough data to contribute to the progress of A.I. in healthcare?  What if privacy concerns don’t allow hospitals to share medical records with companies? That’s when synthetic data comes in. Is synthetic data fake? It is fake but it’s based on real-life data. Moreover, it’s possible to use methods that ensure that synthetic data very much resembles the real one. One of these methods is called generative adversarial network (GAN). ...
Source: The Medical Futurist - Category: Information Technology Authors: Tags: Artificial Intelligence in Medicine Healthcare Design Security & Privacy data privacy A.I. bias synthetic data GAN Source Type: blogs