Sorting out AI, ML, DL, and NLP

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Posted By: Roberta Mullin February 13, 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.

Artificial Intelligence at HIMSS19

Highlights from Twitter Hashtag: #smartHIT

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For years Dr. Nick van Terheyden aka Dr. Nick, has served as a voice on the impact of new technologies on healthcare, earning a reputation as a leading authority on where the future of medicine is going. Combining powers of observation and real world experience, Dr. Nick has seen many predictions come true and makes the case that innovations in healthcare can be accomplished incrementally, not just by moonshot events. On this episode of The Incrementalist, Dr. Nick talks to Khan Siddiqui, MD (@drkhan) CMO for Higi. GPS innovation, medical imaging and the fact that this created technology now used in the Kinect and Gaming AI is better than a 5th Grader. The Higi Insights and potential for this data and its impact on health.

Currently On Air – Voices in Value-Based Care – Tune in to hear value-based programs expert Beth Houck and her guests discuss the challenges, opportunities, and best practices for reporting under MACRA’s Quality Payment Program. Airing now, Beth is talking 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.

Listen to this show weekdays at 1:00pm ET, and rebroadcasts at 5:00am, 1:00pm and 9:00pm ET every weekday.

To Read

SCIO Health Analytics
Drowning Under a Deluge of Data? 5 Ways Machine Learning Can Help – The healthcare industry is amassing more data than ever before. Consider this: The U.S. healthcare system was already producing 150 exabytes of data several years ago and was expected to soon generate zettabytes (1021 gigabytes) and eventually yottabytes (1024 gigabytes) of data.

In the News

Change Healthcare Unveils Claims Lifecycle Artificial Intelligence
Change Healthcare (@Change_HC) announced Claims Lifecycle Artificial Intelligence, a new capability being integrated into the company’s Intelligent Healthcare NetworkTM and financial solutions, to help providers and payers optimize the entire claims processing lifecycle.

Perception Health On AWS Marketplace Machine Learning And Artificial Intelligence Discovery Page
Perception Health (@PerceptionHeal), a provider of healthcare market prediction software, announced their inclusion on the new machine learning (ML) and artificial intelligence (AI) discovery page on AWS Marketplace.

Events

AI Solve: Healthcare – Webcast Replay
Recorded March 21, 2018 at UCSF in SanFrancisco
View the recording

AI is already beginning to shape the healthcare industry, Intel brought together some of the leading minds in the space. At the event called Intel SOLVE: Healthcare, in San Francisco, Intel brought together researchers from Harvard, Princeton, Stanford, GE Healthcare, Optum, Mayo Clinic, The MIT/Harvard Broad Institute and more to talk about the work they are doing with AI.

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.