AI, Machine Learning as a Service Set to Overhaul Healthcare 7wData

Relatively few healthcare organizations have the resources or analytics maturity to develop their own intricate big data analytics infrastructure from scratch, but a growing number of vendors are starting to make the daunting and costly process easier by offering Artificial Intelligence and machine learning as a service (MLaaS). The "as a service" industry, which has quickly branched out to cover a number of critical data-heavy use cases, allows organizations to contract with third-party vendors that do the heavy lifting in terms of data collection, storage, movement, and analytics. Many healthcare stakeholders are already familiar with MLaaS technologies, even if the acronym itself is new to them. On the consumer side, voice-driven personal assistants like Siri, Alexa, Cortana, and Google Home use machine learning techniques to create smart environments and automate technical tasks. In the enterprise space, IBM Watson's commercialized analytics and precision medicine services are a good example, as is Partners Healthcare's IDEA platform, which uses data lake technology to streamline the development of research projects targeting a number of high-value use cases.