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    Cognitive computing shakes up healthcare: What execs need to know

    For many people, their first exposure to artificial intelligence (AI) was seeing IBM’s Watson supercomputer beat Ken Jennings on Jeopardy in 2011. Since then, the concepts that power cognitive computing and AI have grown to include substantial healthcare advancements.

    Cognitive computing is technology that uses artificial intelligence to make predictions based on data. Artificial intelligence is technology that uses reasoning, natural language processing, machine learning, and even human interaction through speech and vision interactions. What makes cognitive computing systems so smart is that they evaluate patterns from data and get better with each use. The goal is for systems to be able to anticipate problems and behavior, offering suggestions and solutions before an issue occurs.

    “Cognitive computing is basically predictive analytics. It analyzes patient data and indicates results and a suggested plan that a doctor can use to decide a course of action,” says Jaspinder Grewal, CEO of CareSkore, a population health management technology company that utilizes artificial intelligence. “Artificial intelligence takes that a step further by leveraging adaptive computing algorithms to formulate the best course of action and, within constraints imposed by the practitioner, implements that action. Cognitive computing acts as an advisor. Artificial intelligence takes that a step further by acting as an assistant.”

    Big names in technology including IBM, Microsoft, and Google have made significant investments in finding healthcare uses for cognitive computing, and providing a platform for various startup firms that create specialized applications.

    The healthcare cognitive computing market will be more than $5 billion by 2022, according to a 2016 study by Grand View Research, Inc. Fifty-two percent of the current market resides in North America, with increased demand for personalized medical care, pressure to reduce healthcare costs, and the rapid growth of technology in healthcare being drivers to innovation.

    With an increased focus on finding solutions for people with chronic conditions, coupled with policy decisions that aim to decrease healthcare costs, it is imperative that health systems understand and begin to utilize cognitive computing systems to meet the demands of the changing healthcare landscape.

    AI landscape

    First, a brief history lesson to understand the evolution of AI in healthcare. After Watson’s appearance on Jeopardy in 2011, IBM began working with health systems in 2012 to enhance oncology treatments and with medical colleges to expand learning.

    In 2015, IBM Watson Health was established, and the company began partnering with Johnson & Johnson, Apple, and Medtronic, and acquiring other technology companies. Apple’s HealthKit and ResearchKit both use IBM Watson technology.

    In February 2017, Microsoft announced the Healthcare NExT initiative based on collaborations that will leverage cloud technology to generate insights about patient health and adherence, make quicker samples to answer processes for genome analysis, and enhance conversational health tools. Other Microsoft AI technology aims to use predictive analysis, rules management, and other best practices to lower healthcare fraud and waste.

    Next: AI tech startups

     

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