Sorting out AI, ML, DL, and NLP

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Posted By: Roberta Mullin April 28, 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 Tell Me Where IT Hurts, host Dr. Jay Anders interviews Tim O’Connell, MD and CEO and founder of Emtelligent, a deep-learning-based medical natural language processing (NLP) company. Together they discuss the differences between AI and NLP, along with NLP’s role in health technology now and in the future. Dr. Anders and Dr. O’Connell get into topics ranging from the current excitement around so-called “ambient NLP”, to the benefits and challenges of the technologies, to capabilities that the big vendors don’t quite have yet. If you’re interested in speech and NLP in health IT, this is a must listen.

In the News

Lenovo Accelerates Artificial Intelligence with Ready-to-Deploy AI Solutions
Lenovo (@Lenovo) Infrastructure Solutions Group (ISG) announces the expansion of its partner ecosystem and launches five new ready-to-deploy artificial Intelligence (AI) solutions. This growing global ecosystem of industry-leading independent software vendors (ISVs) enables Lenovo to bring to market AI solutions for a wide range of applications and industries, including manufacturing, healthcare, retail, and financial services.

Perimeter Medical Imaging AI Announces Important Milestone in ATLAS AI Project with Standalone AI Algorithm Achieving Key Performance Metrics
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 high unmet medical needs, announced significant progress within its ATLAS AI Project, an initiative aimed at advancing Perimeter’s next-gen artificial intelligence (AI) and machine learning tools through clinical development. Perimeter’s proprietary “ImgAssist” AI technology has now been trained with more than 400 volumes of images of excised breast tissue collected during the first stage of its ATLAS AI project.

AccentCare Deploys the Jvion CORE™ to Prevent Avoidable Readmissions
Jvion(@JvionHealth), a clinical artificial intelligence (AI) company, announced that AccentCare (@accentcare), a nationwide company in post-acute healthcare services with over 240 locations in 29 states, will leverage Jvion’s prescriptive clinical AI CORE to focus resources on patients with an avoidable risk of readmission post-discharge. The CORE will provide inferences on how social determinants drive patients’ risk of readmission, as well as recommendations for patient-centric interventions to address these risk drivers.

Galva Pharmacy is First U.S. Pharmacy to Use AI to Improve Drug Matching and Usability of Rx Instructions in E-Prescriptions
Galva Pharmacy in Galva, Ill., recently became the first pharmacy in the country to deploy an in-workflow, artificial intelligence (AI) solution that accurately structures, codifies, and backfills information gaps in electronic prescriptions. The independent pharmacy in Northwest Illinois is using DrFirst’s (@DrFirst) patented AI solution, SmartSuite, within its Speed Script pharmacy management system (PMS) to improve accuracy and efficiency, allowing pharmacy staff to spend more time with patients.

To Read

Can AI Reinvent Radiation Therapy for Cancer Patients? – By John Halamka and Paul Cerrato – Of all the advances in health care artificial intelligence (AI), medical imaging is probably the most remarkable success story. Two prominent examples come to mind: Machine learning has helped improve the screening and diagnosis of retinal disease and is making inroads in skin cancer detection. Given these developments, it’s not surprising to find researchers and clinicians developing the digital tools to improve radiotherapy, which combines imaging technology with high doses of ionizing radiation, delivered through a device called a linear accelerator.

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.