There is an emerging solution for standardizing healthcare data. FHIR utilizes a set of modular components, known as ‘Resources,’ which can be assembled into working systems that will facilitate data sharing within the EHR and...

Data standardization is critical for aggregating data from different sources to train and use AI algorithms. Data standardization refers to the process of transforming data into a common format that can be understood across different...

The GDPR will affect AI implementation in healthcare in several ways. First, it requires explicit and informed consent before any collection of personal data. Informed consent has been a long-standing component of medical practice (unlike...

To create large and diverse datasets used for training algorithms that will perform as planned in clinical practice, you need data from multiple institutions. This will minimize the chance of using data that is too...

If there is one issue that needs to be front and center in AI will fulfill its potential, it is the issue of data: getting enough of it to train the algorithms, having a steady...