Sorting out AI, ML, DL, and NLP

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Posted By: Roberta Mullin May 8, 2019

The alphabet soup of acronyms in the world Artificial Intelligence. What are they? What do they mean? What is the difference between them? This is our ongoing reporting on AI and how it is being integrated into healthcare technology. We are seeking out the thought leaders and innovations that are moving the needle forward using artificial intelligence. Read more posts on Artificial Intelligence in Healthcare.

Follow the hashtag #AIinHealthcare.

Listen

Tune in to Voices in Value-based Care to hear value-based programs expert Beth Houck (@bahouck) and her guests discuss the challenges, opportunities, and best practices for reporting under MACRA’s Quality Payment Program. On this episode, Beth talks to Dr. Michael Sanders, CMIO at Flagler Hospital (@FlaglerHospital) in Saint Augustine, Florida. Hear about how the hospital implemented AI and are seeing reduction in costs, length of stays, and readmissions. The successful program has brought clinician buy in and participation beyond expectation. Now even the community has started to buy in. Learn why Dr. Sanders thinks the Community Hospital of today is creating the next generation of health care.

To Read

Optum IQ
View their interactive infographic, How is Artificial Intelligence Working for Health Care? Artificial intelligence (AI) has a lot of hype surrounding it — and for good reason. Questions abound about the practical value for AI in today’s health care world. Use the interactive infographic to learn more about what AI is and how it is making an impact. Explore the opportunities where its applications can truly make a difference for both health care organizations and consumers.

HealthEC
Predicting the Likelihood of Diabetic Patient Hospital Readmission with AI Solutions – HealthEC is transforming health care with industry-leading population health management (PHM) and value-based care solutions. But our latest innovation will do something truly unique to align with the industry’s growing focus on personalized health. And if we play our cards right, it could also result in a nice reward from CMS. Currently in the testing phase, we expect to unveil a solution by year end that will identify key factors that influence hospital readmission for diabetes and predict the likelihood of diabetic patient readmission. With preliminary results showing the solution being more than 90 percent accurate, we are very enthusiastic about its future success.

Orion Health
AI Day 2019: Building trustworthy AI for the future – Last week, I attended and presented at AI Day, New Zealand’s premier artificial intelligence event in Auckland. The variety of speakers from different industries from finance, to housing and education, was a clear indication of how AI really is everywhere.

In the News

Gestalt Diagnostics Announces Artificial Intelligence Algorithm that Triages and Routes Cases
Gestalt Diagnostics announced their development of an artificial intelligence algorithm that identifies and routes more critical cases first to the appropriate pathologist based upon a pathologist’s specialty.

Artificial intelligence comes to healthcare just in time to stem the tide of RN turnover and take advantage of Millennials’ online predilection
Artificial intelligence (AI) is a core solution for the current tight labor market for nurses and is especially tailored to the trends seen in the younger generation of workers, who tend to interact in the job market using technology, David Leonard, senior vice president of growth for Arena (@arenadotio), told attendees at the American Organization of Nurse Executives’ annual conference recently.

Events

To Follow
The Basics and Resources

From the leading text book around the world, Artificial Intelligence: A Modern Approach.

Artificial Intelligence is composed of six different disciplines:

  1. Natural Language Processing to enable it to communicate successfully in English
  2. Knowledge Representation to store what it knows or hears
  3. Automated Reasoning to use the stored information to answer questions and to draw new conclusions
  4. Machine Learning to adapt to new circumstances and to detect and extrapolate patterns
  5. Computer Vision to perceive objects
  6. Robotics to manipulate objects and move about

To build a generally intelligent agent, you need machine learning in addition to the other aspects mentioned above.

Machine Learning is roughly the science of prediction. Given certain knowns (features), you wish to predict some unknowns (targets). The unknown could be structured (e.g. numeric) or unstructured (e.g. a string response).

Deep Learning is a sub field of machine learning where concepts are learned hierarchically. The simplest concepts emerge first, followed by more complicated concepts that build on the simpler ones. Usually, this leads to a simple layered hierarchy of concepts.

Optum Resource Library

Natural Language Processing: AI with an ROI
Health care providers need to see a return on any analytic investment they make. Natural language processing (NLP) is one way AI can help providers convert the potential within their health data into quality improvement and cost savings. Natural language processing is an AI technology that actually makes sense for health care.

IBM Analytics

Navigating the A.I. and Cognitive Maze – If you work in the area of Artificial Intelligence (AI) and Cognitive Computing, you might use buzz words and phrases which to others might be perceived as confusing jargon. This article attempts to explain what these terms mean, how they relate to one other and where they all fit along the AI and cognitive time continuum. I include a glossary of my top 20 useful AI/cognitive terms — and advice on getting started on your AI/cognitive journey.