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Predicting the Unpredictable – MLaas

Machine learning and Prediction

Predictive analytics in healthcare has been one of the fastest growing trends in recent years and it is scaling up over the next three. With this industry top of mind in the news and those closest to it; patients, providers, and insurance companies realizing the penultimate benefits of relative data, healthcare analytics is a solid foundation for anyone interested in the field of analytics. Beyond collection and analysis is the deeper dive of meaningful use in regard to artificial intelligence (AI) and machine learning within datasets and analysis.

Smart Health and Wellbeing

Though big data in healthcare analytics has previously lagged behind other industries, it now faces a massive upheaval. Over the last ten years or so, simply moving patient’s records to electronic health records (EHR) and storing them in the cloud for at-your-fingertip information, is the tip of the iceberg.

Big data in healthcare has grown up. Researchers and providers are able to make more informed decisions, more quickly gleaning information from such records and using the data to predict diseases, make better diagnoses, and determine patterns. Some of these patterns are especially useful in patient empowerment and support for such chronic diseases as Alzheimer’s, cancer, diabetes, and Parkinson’s.

As complex as the healthcare system is, few healthcare organizations have the resources or skilled personnel to develop and analyze such intricate data. There is a shift, however, in the application and access of big data healthcare analytics and that is an entry in the as-a-service industry.

Healthcare Tech in the Cloud

The advent of cloud computing has made it possible for organizations with limited resources – skilled personnel and in-house knowhow – to progress their health management programs. Cloud-based tools and applications allow organizations to reduce infrastructure and development frustrations to focus on value-based care.

The machine learning as a service market is skyrocketing and at a growth rate of 38.40 percent annually is expected to be worth $20 billion in the next 20 years or so. This sets machine learning as a service industry in healthcare on a trajectory of $5.4 billion by 2022, according to a 2016 report.

Machine Learning as a Service combine with artificial intelligence could bring over $46 billion to MLaas vendors could revolutionize healthcare by 2020. Driven by big data analytics, healthcare organizations may find cloud-based tools and machine learning applications easier on the budget with a broad range of proactive measure capabilities in the industry.

This year, the driving force behind most of the artificial intelligence spending is in quality management, diagnosis and treatment systems, customer service, and security of data. According to a survey conducted by Silicon Valley Bank last year, healthcare AI is expected to the most influential technology in 2017.

In a rapidly changing environment, both technologically and organically, the analytics required to succeed in the healthcare industry may lie in machine learning as a service. This as-a-service focus may also be a cost effective way to engage the large, complex amounts of data derived from the players in the healthcare industry.

If you’re interested in contributing to the future of big data, we might have the role for you. We specialize in Data and Analytics recruitment and always have a wide range of vacancies at both junior and senior level. Take a look at our current vacancies or contact us to find out more.

For the East Coast and Mid-West teams please call 212-796-6070, or email

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