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 Ted Willich CEO NLP Logix about GPS technology and its impact and using AI to identify lesions in x-ray images to next generation OCR.

In the News

CyberLink Integrates FaceMe® AI Facial Recognition into iMedtac’s Smart Medicine Cabinet
CyberLink Corp. (@CyberLink), a pioneer of AI and facial recognition technologies, announced that its FaceMe® AI facial recognition engine has been integrated with iMedtac’s Automatic Dispensing Cabinet. This smart medicine cabinet is powered by IoT and facial recognition technology, integrating into an AIoT iHospital service platform and enhancing pharmaceutical management.

Zebra Medical Vision Announces Agreement With DePuy Synthes to Deploy Cloud Based Artificial Intelligence Orthopaedic Surgical Planning Tools
Zebra Medical Vision (@ZebraMedVision), the deep learning medical imaging analytics company, announces a global co-development and commercialization agreement with DePuy Synthes* to bring Artificial Intelligence (AI) opportunities to orthopaedics, based on imaging data.

DrFirst’s Patent-Pending AI-Based Technology Solves Major Hurdles to Medication Reconciliation: Missing Information and Unstructured Data
DrFirst (@DrFirst), the nation’s leading provider of e-prescribing, patient medication management, and price transparency solutions, announced that it will be awarded a second U.S. patent for its SmartSuite technology. The U.S. Patent and Trademark Office’s (USPTO’s) Notice of Allowance for a patent (application no. 14/972,209) is for SmartSig’s “method and system for intelligent completion of medical records based on big data analytics.”

Secure Exchange Solutions Automates Clinical Data Analysis Evaluation to Help Solve the Prior Authorization Challenge for Provider and Payer CIOs
Secure Exchange Solutions (SES) (@Secure_Exchange) a provider of cloud-based clinical data exchange and Artificial Intelligence (AI) powered technologies, is helping organizations solve the prior authorization challenge by integrating secure data exchange and analysis solutions into existing workflows. The value delivered is significant as it improves efficiencies.

Nuance Transforms Radiology Reporting With Major AI and Ambient Enhancements to PowerScribe One Cloud Platform
At the Radiological Society of North America’s (RSNA) 105th Scientific Assembly and Annual Meeting, Nuance Communications, Inc. (@NuanceInc) announced the addition of multiple AI-driven cloud innovations in the new release of PowerScribe One, the radiology reporting solution used by approximately 80% of U.S. radiologists. PowerScribe One transforms the radiology reading experience with AI-assisted reporting and decision support, real-time data synchronization with third-party systems, and a new user experience to improve efficiency, alleviate radiologist fatigue, and advance care quality.

GE Healthcare Expands Intelligent Health Ecosystem with Launch of Edison Developer Program to Ease AI Adoption for Providers
GE Healthcare (@GEHealthcare) launched the Edison Developer Program to accelerate the adoption and impact of intelligent applications and developer services across health systems. The program is based on Edison, GE Healthcare’s secure intelligence platform, and helps healthcare providers gain easier access to market-ready algorithms and applications by directly integrating these technologies into existing workflows.

HPE and Cray Unveil Comprehensive, Next-Generation HPC and AI Solutions Optimized for the Exascale Era
Hewlett Packard Enterprise (HPE) (@HPE) announced it will deliver the industry’s most comprehensive high-performance computing (HPC) and Artificial Intelligence (AI) portfolio for the exascale era, which is characterized by explosive data growth and new converged workloads such as HPC, AI, and analytics.

To Read

GE Healthcare
How Artificial Intelligence Could Impact Breast MRI
New developments in artificial intelligence for breast MRI could help unlock efficiencies for radiologists while improving the patient experience for the most common type of cancer. The power of artificial intelligence (AI) in healthcare has already revealed highly promising advancements that touch on nearly every field of medicine—from identifying patterns that indicate sepsis1 to detecting major events like a collapsed lung.

The Human-Centric Rise of Artificial Intelligence in Healthcare
Dressing one morning, as she usually does, Jane notices a strange skin discoloration on her arm. Still smaller than a dime, but she swears it used to be half that size and certainly more symmetrical. She asks her virtual assistant to scan the area and assess. A camera built into her bathroom mirror fires up, captures photos, and checks them against archival images from Jane’s entire photo library. Jane was right; something is wrong. The artificial intelligence maps the images against troves of curated diagnostic data. In seconds, the AI offers a diagnosis with 95 percent accuracy, schedules an appointment with a specialist, and asks Jane if she’d like to share the images and her recent biometrics directly with the medical practice.

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.