Healthcare institutions continue to transform at full speed due to the recent disruption. While organizations are putting a major focus on data, many are incorporating machine learning (ML) in medical device deployment. ML can analyze a wide range of data and create models used to meet a vast array of analytic and operational requirements. While ML can deliver improved outcomes, it can be difficult to use.

 According to a report from the U.S. Bureau of Labor Statistics, there are less than 32,000 data scientists in total in the U.S. While ML requires experts – this shortage makes a big impact. Other challenges organizations face include aggregating and transforming clinical and device data in one platform and performing ML where the data lives in safe, secure, and fast environment. How can you develop applications that perform intelligent prescriptive programmatic actions in response to real-time events? How can you gain critical competitive advantages and business benefits? How can you be first to market with a new product or service?

 Join InterSystems and a select group of industry experts to discuss how medical device manufacturers are looking to use machine learning, and where both challenges and opportunities exist.