Posted by:Shyam Deval January 27th, 2017

A report from research firm IDC has thrown more light on the emerging importance of Artificial Intelligence (AI). According to a new Worldwide Semiannual Cognitive/Artificial Intelligence Systems Spending Guide, spending on AI technologies is all set to surge from $8 billion in 2016 to $47 billion in 2020.1

With healthcare being one of the industries that will invest the most on cognitive/ AI systems, it is apparent that this industry is betting big on AI technologies. Virtual assistants, intelligent automation and cognitive computing all are going to impact various facets of healthcare – from operations to patient-centric care to precision medicine.

Data is a huge driving force in the world of healthcare today.

EHR systems have largely aided the digitization of health records within most major hospitals and practices today. Added to this data is the newly minted “patient-generated health data” which is gathered through mobile health apps and wearables. Remote monitoring systems can also help transmit data through sensors and devices.

Other players in the healthcare ecosystems like clinical and medical research firms are also leveraging technology in recruiting a greater number of participants in clinical trials and medical research studies. Apple’s revolutionary ResearchKit, an open source software framework that helps in the development of mobile apps for research, ResearchStack, Ionic ResearchKit are all contributing to the immense growth of patient-generated data. Read more about mobile research apps here.

But with the availability of so much data, the real quandary is being able to use such data to involve patients more in care by coming up with personalized diagnosis and treatment plans. AI can help.

Machine learning and deep learning algorithms, visualization, rich media analytics and cognitive software platforms can facilitate healthcare’s transition to a value-based care model. In addition, AI has the potential to analyze and identify patterns in huge data sets that can help address some crucial pain points and help improve quality and efficiency of care.

Surgical robots, training of healthcare professionals, speech recognition, data crunching – the uses of AI are many. The future will increasingly see AI unlocking the insights hidden in data, improving efficiencies and enabling patient-centric care models in the healthcare industry.


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