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.


From The Incrementalist, host Dr. Nick van Terheyden aka Dr. Nick talks to Matt Seefeld the EVP at Medevolve about analytics and machine learning to manage revenue cycle more efficiently and the end of the EHR craze.

In the News

Medidata Institute and Project ALS Launch Partnership to Accelerate New Treatment Strategies
Medidata (@Medidata), a Dassault Systèmes company, and the global leader in creating end-to-end solutions supporting the entire clinical trial process, announced the launch of a research partnership between the Medidata Institute and Project ALS (@ProjectALSorg). The program is designed to gain a greater understanding of the ALS disease process and develop new therapeutic strategies. Launches Practical Artificial Intelligence Solutions for Resource-Constrained Physicians (@SingularityAIUS), a new company delivering integrated workflow solutions for physicians, announced the release of its first product, the EmPathSmart Camera™, an AI-enabled box-top for a microscope to provide end-to-end support to aid pathologists with their most time-consuming tasks, such as cell counting and grading.

PhysIQ and U.S. Veteran’s Affairs Publish Breakthrough Study Predicting Heart Failure Hospitalization up to 10 days in Advance using AI
physIQ, Inc. (@PhysIQ) and the US Department of Veteran’s Affairs (VA) published the results of a breakthrough study aimed at validating the ability to detect the onset of heart failure exacerbation using wearable sensors and machine learning-based personalized physiology analytics.

Replete® Brings Consumers One-Click Access to their Health and Care Data, Partners with CommonWell Health Alliance® to provide access to the consumer’s data
Replete® (@repletehealth) is proud to announce its launch into the health-tech market with a first-of-its-kind mobile application that will allow consumers to access their health data, including electronic health records, lab tests results and vaccination and immunization records, as well as help consumers track and maintain their health goals. The app features cutting edge artificial intelligence (A.I.) and machine learning that will detect the decline of clinical efficacy of any treatment/medications based on a consumer’s feelings and nudge them and their physician to act upon the health changes.

Research Shows Machine Intelligence Can Dramatically Reduce Emergency Department Visits for Millions of Medicare Members
Health at Scale (@healthatscale), the leader in machine intelligence for care optimization, released a report, Precision Interception: Machine Intelligence for Actionable Prediction and Prevention of Emergency Department Visits, detailing the findings of a study conducted by its research team. The study examined profiles of more than two million Medicare plan beneficiaries to understand how Health at Scale’s technology could leverage machine intelligence for precision interception to reduce emergency department visits in the future.

Utilizing Artificial Intelligence to Synchronize Stroke Care Impacts Workflow and Hospitalization (@viz_ai), Inc. the leading applied artificial intelligence healthcare company, is excited to highlight real-world data from Dr. Ameer Hassan’s presentation “Early Experience Utilizing Artificial Intelligence Shows Significant Reduction in Transfer Times and Length of Stay in a Hub and Spoke Model.”

The Innovator in AI Enhanced Stroke Imaging Officially Becomes RapidAI
iSchemaView, also known as RAPID, the worldwide leader in advanced imaging for stroke, announced the company is now RapidAI (@RapidAI). In 2018, co-founder Dr. Greg Albers presented groundbreaking findings at the International Stroke Conference (ISC) that supported expanded treatment window guidelines for stroke patients.

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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.