Sorting out AI, ML, DL, and NLP

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Posted By: Roberta Mullin March 31, 2021

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.

To Listen

From The Incrementalist, host Dr. Nick van Terheyden, aka Dr. Nick, talks to Shivdev Rao, MD the CEO of Abridge, an AI company that raised $15M to help patients transcribe doctor appointments. They discuss using NLP, AI and ML to extract useful information from conversations between patients and doctors.

In the News

Perimeter Medical Imaging AI Announces Clinical Study at Northern Arizona Healthcare Verde Valley Medical Center
Perimeter Medical Imaging AI, Inc. (@PerimeterMed), a medical technology company driven to transform cancer surgery with ultra-high-resolution, real-time, advanced imaging tools to address areas of high unmet medical need, announced that Dr. Beth DuPree, a surgeon at Northern Arizona Healthcare Verde Valley Medical Center, expects to enroll up to 100 patients in a study that will evaluate the use of Perimeter’s Optical Coherence Tomography (OCT) Imaging System during breast conserving surgery.

Marpai Health to Acquire Continental Benefits Launching the First Smart Health Plan System
Marpai Health, Inc. (@marpaihealth), a global company in deep learning, the most advanced form of artificial intelligence, announced it has entered into a definitive agreement to acquire third-party administrator Continental Benefits, LLC. Marpai brings deep learning to self-insured health plans, which will allow for the processing of comprehensive data to increase quality care, reduce costs, simplify the healthcare experience, and empower plan members to live healthier lives. The transaction is expected to close in April 2021.

RSIP Vision Unveils Robust Metal Implant and Anatomical Segmentation Tool, for Improved Planning of Specialized Orthopedic Procedures including Revision Arthroplasty
RSIP Vision (@RSIPvision), an innovator in medical imaging through advanced AI and computer vision solutions, announces an advanced joint segmentation tool for detailed, non-invasive planning of revision arthroplasty and other orthopedic procedures for patients with pre-existing metal implants. This powerful AI-based software module enables quick and accurate segmentation of different joints from CT scans of hips, knees, shoulder and spines. It provides precise measurements of the geometry of joints, including complicated cases of joints with existing metallic orthopedic implants.

Thermo Fisher Scientific Collaborates with Artificial to Enhance COVID-19 Diagnostic Testing Solution
Thermo Fisher Scientific (@thermofisher), the world leader in serving science, and Artificial, developers of flexible automation software, have announced a strategic technology collaboration to develop an integrated and comprehensive software automation platform for Thermo Fisher’s standardized COVID-19 Testing Platform. The integration will result in increased testing throughput and support global healthcare initiatives.

New Data on Stroke Care Show the Impact of Viz.ai’s Artificial Intelligence-Powered Platform on Patient Outcomes
Viz.ai (@viz_ai) announced new data supporting the use of its technology to coordinate care for acute ischemic stroke, hemorrhagic stroke, and clinical trial recruitment at the 2021 International Stroke Conference. Dr. Ameer E. Hassan of the Valley Baptist Medical Center in Texas presented two studies utilizing Viz LVO to improve care coordination for ischemic stroke patients requiring treatment across health systems and at a stand-alone center.

Health Catalyst Launches New Healthcare.AI™ to Deliver Augmented Intelligence at Scale to Healthcare Industry
Health Catalyst, Inc. (@HealthCatalyst), a provider of data and analytics technology and services to healthcare organizations, announced the launch of the new Healthcare.AI™. Created to address healthcare business opportunities and challenges across revenue, cost, and quality, the Healthcare.AI suite of augmented intelligence (AI) products and services will significantly expand the effective use and use cases of AI in healthcare.

To Read

The Future of the Healthcare Job Market – Artificial Intelligence (AI) & Virtual Technologies – From Clarke Caniff Strategic Search – The health care job market came into real focus in 2020 after the global COVID-19 pandemic disrupted the entire global workforce. As the entire global population leaned on the expertise of the health care industry, the sudden increase in demand for health care services triggered by COVID-19 meant that opportunities for meaningful and rewarding careers in healthcare became viable for a large population of job seekers.

Diabetes Meets Machine Learning, Part 2 – By John Halamka and Paul Cerrato – In February, we discussed the benefits of using machine learning (ML) to improve screening for diabetes and for managing the disorder. In some situations, ML can more accurately detect the presence of prediabetes, for instance. Similarly, there’s research to show that the right algorithms can improve the treatment of Type 1 diabetes.  But there’s also mounting evidence to suggest ML can benefit Type 2 patients.

Matthew Lamons

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.