Sorting out AI, ML, DL, and NLP

TOPICS:

Posted By: Roberta Mullin July 31, 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 Harlow on Healthcare to hear healthcare attorney and award-winning blogger David Harlow and his guests discuss the critical issues shaping the future of health IT and healthcare at large. From cybersecurity to AI, precision medicine to health reform, if the topic is trending Harlow is on it. On this episode, David interviews Clemens Suter-Crazzolara, VP Product Management, Health and Precision Medicine at SAP & talk about the ethics and biases of artificial intelligence and the balance between human and machine intelligence in the long term, and building simple chatbots and then other more sophisticated AI tools in the near term.

To Read

In the News

Beazley and PeriGen to Collaborate on Patient Safety Programs Addressing Obstetric Safety
PeriGen (@PeriGen), the global leader in developing artificial intelligence (AI) systems for obstetrics, has partnered with specialist insurer Beazley (@BeazleyGroup) to offer its safety-based obstetric program to Beazley’s healthcare clients in the United States. Under the arrangement, Beazley will facilitate distribution of PeriGen’s AI-powered early warning system for labor and delivery, PeriWatch Vigilance®. The system works alongside any existing electronic fetal monitor and assesses long-term trends in fetal heart rate, contractions, maternal vitals and labor progress to provide bedside clinicians with a steady, real-time flow of risk management information.

Catasys Launches Breakthrough AI Capability to Address Chronic Disease
Catasys, Inc. (@catasys), an AI and technology-enabled healthcare company, announced Catasys PRETM (Predict-Recommend-Engage). Catasys has long been recognized as the leader in utilizing a sophisticated algorithm to identify care avoidant members who have untreated behavioral health conditions. Now, Catasys is launching an evolved model—Catasys PRE—which applies the Company’s capabilities beyond behavioral health conditions to chronic conditions including, as examples, cardiovascular disease, diabetes, and pulmonary disease.

Research Collaboration Between U-M and Atomwise to Accelerate Drug Discovery Using Innovative Artificial Intelligence Approach
From making pain management safer and more effective to identifying inhibitors for a fibrosis target protein and more, researchers from Michigan Medicine (@umichmedicine), as well as the University of Michigan College of Pharmacy and U-M Life Sciences Institute, are looking to advance their projects through Atomwise’s Artificial Intelligence Molecular Screen (AIMS) Awards program, which uses AI-powered screening technology employed by large pharmaceutical companies.

BlackThorn Therapeutics Closes $76 Million Series B to Advance Targeted Therapeutics for Mental Health
BlackThorn Therapeutics, a clinical-stage, neurobehavioral health company pioneering next-generation artificial intelligence (AI) technologies to advance targeted therapeutics, announced the close of its $76 million Series B financing.

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.

American Hospital Association

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.