Healthcare IT News May 26, 2021
An expert discusses use cases for this emerging approach, and describes how it’s poised to enable big advances in decision support, diagnosis, surgery and more.
Today there is a bottleneck in the development of artificial intelligence and machine learning – real-world data collection. AI and machine learning models require large datasets to become proficient at a task.
But preparing these datasets for model training is both costly and labor intensive. It is a conundrum, and the lack of large, accurately labeled datasets for specific applications is holding back the development of artificial intelligence and machine learning.
Some say synthetic data offers a solution – data that imitates real-world data. Instead of manually collecting and labeling datasets from the real-world, synthetic...
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