Artificial intelligence, cognitive computing and machine learning are coming to healthcare: Is it time to invest?

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The arrival of artificial intelligence and its ilk -- cognitive computing, deep machine learning -- has felt like a vague distant future state for so long that it's tempting to think it's still decades away from practicable implementation at the point of care. And while many use cases today are admittedly still the exception rather than the norm, some examples are emerging to make major healthcare providers take note. Regenstrief Institute and Indiana University School of Informatics and Computing, for instance, recently examined open source algorithms and machine learning tools in public health reporting: The tools bested human reviewers in detecting cancer using pathology reports and did so faster than people. Indeed, more and more leading health systems are looking at ways to harness the power of AI, cognitive computing and machine learning. "Our initial application of deep learning convinced me that these methods have great value to healthcare," said Andy Schuetz, a senior data scientist at Sutter Health's Research Development and Dissemination Group.


Deep Learning/Computer Vision Data Scientist - McLean, VA

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Booz Allen Hamilton has been at the forefront of strategy and technology for more than 100 years Today, the firm provides management and technology consulting and engineering services to leading Fortune 500 corporations, governments, and not-for-profits across the globe. Booz Allen partners with public and private sector clients to solve their most difficult challenges through a combination of consulting, analytics, mission operations, technology, systems delivery, cybersecurity, engineering and innovation expertise. Key Role: Apply technical and analytical expertise to exploring and examining data from structured, semi-structured, and unstructured data sources and types, including text, audio or signal, and image or video. Leverage a proven track record of serving as the client interface and experience with developing cutting-edge solutions using advanced machine learning, deep learning, and computer vision. Supervise the activities of others, as needed.


Harvard Business School Is Teaching MBAs About Artificial Intelligence, Deep Learning -- Here's Why

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At Harvard Business School (HBS), MBA students are pondering a future when robots rule the road. The pioneers of the driverless car movement -- such as Google and Tesla -- are mapping the MBAs a future in which artificial intelligence and robotics will likely impact the entire job market and global economy. David Yoffie, professor of international business administration at HBS, believes such disruptive technologies are now an "essential" part of the b-school landscape. "What I'm trying to teach students is: What can these technologies deliver? And what are the challenges and opportunities for a company that does AI?" he says.


Feature engineering headache disappears with deep learning - TotalCIO

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One of the biggest differences between machine learning and deep learning is the effort that goes into making the algorithms work. With machine learning, data scientists have to perform a task called feature engineering. "People get the incoming data, and they prepare it, and they clean it, and they maybe manipulate it in a way that's going to give them the relevant information," said Edd Wilder-James, former vice president of technology strategy at Silicon Valley Data Science and now an open source strategist at Google's TensorFlow, during a presentation at the Strata Data Conference. Looking to establish accountability across disparate project teams? Trying to automate processes or allow for lean methodology support?