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.


On CTO Talk, technology expert Matt Ferrari discusses the issues, challenges, and opportunities transforming healthcare technology today, all from the CTO point of view. Tune in because when CTOs talk, health IT listens. On this episode, Matt talks with John Axerio- Cilies the CTO and co-founder of Arterys, a medical imaging startup connecting practices and disciplines to build more intelligent, accessible and powerful tools for improved patient care. John leads the development of the first cloud platform to gather, process, analyze and report on medical images from anywhere in the world. He is also responsible for leading the company’s deep learning and regulatory teams.

To Read

The Three A’s that Will Define the Future of Patient Access: Automation. Artificial Intelligence. Analytics. – The future of patient access in healthcare will be defined by technology and anchored in the rich triad of automation, artificial intelligence, and analytics…and it’s available today! At the recent National Association of Healthcare Access Management (NAHAM) Symposium, Natalia Arzeno, Chief Data Scientist, and Aakarsh Sethi, Product Manager, from Infinx Healthcare, presented a discussion on the impact of a reshaped and supercharged payment lifecycle and its impact on the business of healthcare.

Harnessing Nontraditional Data Sources Can Drive Better Health Outcomes – How does access to a sidewalk correlate to the risk of premature death? An engineer would likely point to transportation research that highlights the benefits sidewalks provide to pedestrian safety. In health care, sidewalks are just one example of an environmental factor that contributes to an individual’s and a community’s health.

In the News

Belong.Life Launches End-to-End Patient Engagement Platform for Payers, Providers, Pharma and Advocacy Groups (@Belong_Life), creators of the “Belong- Beating Cancer Together” mobile app, the world’s largest interactive social network for cancer patients, caregivers and healthcare professionals, announced the availability of its new breakthrough Patient Engagement Platform (PEP) for all healthcare stakeholders. Designed to improve patient engagement, education, compliance, satisfaction, auto-care coordination and efficiency, the end-to-end solution provides patients, payers, providers, pharma and advocacy groups with hyper-personalized and configurable patient engagement tools, navigation and management services.

HEALTH[at]SCALE Secures Strategic Investment to Advance Precision Delivery of Healthcare with Predictive Machine Intelligence
HEALTH[at]SCALE (@healthatscale), the leader in machine intelligence for care optimization, announced a strategic investment of $16 million in Series A funding. HEALTH[at]SCALE’s machine intelligence is designed by a leading team of current and former machine learning and clinical faculty from MIT, Harvard, Stanford and U-Michigan.


Machine Learning & AI For Healthcare
June 13-14, 2019 Westin Copley Place, Boston MA
Register for this event.

Want to better understand how healthcare is already implementing the use of machine learning and artificial intelligence within their systems? Then don’t miss this event! When it comes to machine learning and AI, healthcare is beyond hype and already seeing the influence of these technologies within workflows. However, the successful implementation that drives results depends on achieving analytics maturity and ensuring data quality and governance. So, for this event, HIMSS is taking a holistic, workshop approach with a focus on implementation. The Machine Learning and AI for Healthcare event is key for anyone looking to drive outcomes and innovation with AI and machine learning.

AI Med Cardiology19

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.