Demystifying AI in Healthcare: A Practical Survey of Machine Learning Technologies 2554

As big data has become more meaningful and valuable to practitioners and researchers, machine learning (ML) and artificial intelligence (AI) have become powerful tools that seem to be ushering in a transformative era in healthcare, with AI having the potential to add very real value to the healthcare sector.

Yet one of the greatest challenge to AI is not limitations in the technologies currently available, but rather ensuring their adoption in daily clinical practice.

To complicate matters, AI is not one technology, but more often a collection of models, methods and tools.
In this symposium presentation, discussion will include popular machine learning techniques driving AI in healthcare. Additionally, AI technologies will be broken down to key elements and core technological processes to illustrate, both, the advantages and the realistic boundaries of these technologies.

The initial discussion will introduce machine learning. Within machine learning, related techniques that will be highlighted are Neural networks, deep learning and expert systems as a part of clinical decision-making support.

A second goal of this lecture is to empower the audience to pursue more in-depth knowledge of any healthcare AI technologies they may individually encounter as part of their healthcare technology initiatives. The audience will also be given strategies to identify areas of strength and weakness of these technologies within their organizations.