Sorting out AI, ML, DL, and NLP

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

Conversations on Health Care is a radio show about reform and innovation in the health care system. Each week, hosts Mark Masselli and Margaret Flinter interview a thought leader from the realm of health policy, health innovation, health technology and global health. On this episode, they speak with Noelle LaCharite, Principal Program Manager for Applied AI and Cognitive Services at Microsoft, and one of the original voice ‘skills’ developers for Amazon’s Alexa.

To Read

RevSpring
Understanding AI and Big Data for Today’s Revenue Cycle – We’ve taken a look at the evolution of big data in the hospital revenue cycle before, but things are evolving quickly, so we decided that it was time to take another pass. This is mostly because artificial intelligence (AI) is emerging as the tech concept that defines how revenue cycle professionals interact with the mountains of data we process. Here’s a look at some of the trends and changes we expect in the future of big data and AI.

Dimensional Insights
Dimensional Insight Book Club: Deep Medicine – They say you can’t replace the human touch, but many believe artificial intelligence (AI) is learning just how. In Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again, Eric Topol examines AI’s role in healthcare and how we may be welcoming a new group of colleagues sooner than we think. Let’s take a look at “Deep Medicine” in today’s Dimensional Insight book club review.

In the News

MedEvolve Introduces New AI-Driven Workflow Automation Solution for Revenue Cycle Management Teams
MedEvolve, Inc. (@MedEvolve), a national provider of data-driven solutions that provide unmatched transparency, automation and accountability for physician practices, announced the availability of MedEvolve RCM Workflow. The solution leverages artificial intelligence (AI) to help providers automate and optimize cash collection, increase staff productivity and accountability and reduce cost to collect.

Integrated Operating Rooms to Grow Exponentially with Virtual Reality and Artificial Intelligence
The operating room (OR) is transforming from a seemingly simple box into a technology-powered, infection-free, and sleek surgical environment. The new-age OR will be able to utilize intelligent and efficient delivery options to improve the precision and predictability of the services offered. This can be made possible through robotic-assisted surgery devices (RASDs), which will greatly help drive the $4.50 billion US and EU5 hospital OR products and solutions market toward $7.04 billion by 2022.

Konica Minolta Healthcare Partners With DiA Imaging Analysis to Offer Advanced AI-based Cardiac Ultrasound Analysis
DiA Imaging Analysis (@DiA_Analysis), a leading provider of artificial intelligence (AI) powered ultrasound analysis solutions, announced that it has partnered with Konica Minolta Healthcare Americas Inc. (@KonicaMinoltaMI), a market leader in medical diagnostic imaging and healthcare IT, to expand analysis capabilities of Konica Minolta’s Exa® Cardio PACS Platform (Cardiovascular Information System) with DiA’s cardiac analysis, “LVivo Toolbox.”

Events

Machine Learning for Healthcare 2019
August 8-10, 2019
University of Michigan, Ann Arbor, MI
Register for this event.

MLHC is an annual research meeting that exists to bring together two usually insular disciplines: computer scientists with artificial intelligence, machine learning, and big data expertise, and clinicians/medical researchers. MLHC supports the advancement of data analytics, knowledge discovery, and meaningful use of complex medical data by fostering collaborations and the exchange of ideas between members of these often completely separated communities. To pursue this goal, the event includes invited talks, poster presentations, panels, and ample time for thoughtful discussion and robust debate.

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.