Artificial Intelligence

One of the most common data analytics questions from providers is how to operationalize machine learning and artificial intelligence, says Rob Wellen, regional vice president at KenSci.

FarmaTrust CEO Raja Sharif says blockchain ensures greater data integrity in areas such as AI, analytics and regulatory reporting, which can increase public confidence in the use of data.

Srinivasan Suresh, MD, VP at UPMC Children's Hospital of Pittsburgh, says start with engaging the clinicians and have a team to standardize care to reduce variation for measurable changes.

Tina Esposito, chief health information officer at Advocate Aurora Health, says her organization's data and analytics heart failure pilot realized a 23 percent reduction in utilization.

Ilia Tulchinsky, engineering director at Google Cloud Healthcare & Life Sciences, explains how an ecosystem of applications that include APIs could enable the free flow of innovation.  

Start with an understanding of what the data quality issues are and the differences in documentation and in workflow from different providers, says Michael Schwarz, executive director of IS at Indiana University Health System.

CHOC Children's CIO Anthony Chang, MD, shares misconceptions of AI and ML in healthcare, explaining why they will actually make the field a more attractive career choice for physicians and radiologists.

The Boston Machine Learning & AI for Healthcare event focuses on how to build healthcare data competency and acquire new AI skills.

Artificial intelligence will become effective in two to three years, although robots will still require human beings, according to Mahmoud Saleh El Halik, the head of Health Informatics at Latifa Women and Children's Hospital.

Data hubs can enable AI research and actionable insights by bringing together different sources of data and reducing organizational data silos, says Esteban Rubens, global principal for enterprise imaging at Pure Storage.