Sorting out AI, ML, DL, and NLP

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Posted By: Roberta Mullin May 26, 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 Healthcare de Jure, host Matt Fisher’s guest is Chief Technology Officer at Wolters Kluwer Health, Jean-Claude Saghbini. Their discussion focuses on advancement of technology to all areas of life and growth within healthcare; creating trust in use of technology through evidence basis and transparency; imperative around access to data and accuracy of data utilized; position of artificial intelligence to augment intelligence; and identifying how technology can be adopted to drive development.

In the News

Intermountain Healthcare, UTHealth in Houston and Rush University Join PhysIQ’s Study to Develop COVID-19 Digital Biomarker
PhysIQ Inc. (@PhysIQ) recently announced that Intermountain Healthcare Utah (@Intermountain), The University of Texas Health Science Center at Houston (UTHealth) (@UTHealth) and Rush University Medical Center (@RushMedical) have joined the NIH-funded DeCODe study to develop an AI-based COVID-19 digital biomarker. These institutions will serve as recruiting centers and key partners in the Phase II validation stage of this study. Realization of this biomarker may provide early detection of a rapid clinical decompensation in high-risk COVID-19 positive patients.

AdventHealth and Sema4 Launch a Data-driven Precision Medicine Program to Optimize Patient Care and Outcomes
AdventHealth (@AdventHealth) and Sema4 (@sema4), a patient-centered health intelligence company leveraging AI and machine learning to derive data-driven insights, announced a wide-ranging collaboration that builds upon the current AdventHealth Genomics and Personalized Health Program to provide new research insights and to prevent, detect and treat disease in their patients.

AR Medical Technologies Launches MaskFit AR: Helping You Sleep for Better Health
Positioned at the forefront of helping people with obstructive sleep apnea (OSA) improve their health and quality of life, AR Medical Technologies launches MaskFit AR (@MaskFitAR). Powered by artificial intelligence and machine learning, MaskFit AR overcomes a 30-year problem of improper patient mask fitment for people who use CPAP or BiPAPTM to treat their OSA. MaskFit AR is much more than just a facial scanner or a measurement tool, it is a next generation mobile app platform that overcomes the guess work of accurate mask fitment which is essential in the treatment of obstructive sleep apnea (OSA).

Sensyne Health Signs Strategic Research Agreement with the Colorado Center for Personalized Medicine
Sensyne Health (@SensyneHealth), the Clinical AI company, announces that it has signed its second Strategic Research Agreement in the U.S. with the Colorado Center for Personalized Medicine, a partnership between non-profit health system UCHealth and the University of Colorado Anschutz Medical Campus (@CUAnschutz). The agreement will enable the ethical application of clinical AI research to improve patient care and accelerate medical research.

Tempus Unveils Its Lens Platform, Offering Unparalleled Access to One of the World’s Largest De-Identified Clinical and Molecular Datasets
Tempus (@TempusLabs), an artificial intelligence and precision medicine company, announced the launch of its cloud-based data and analytics platform, Lens. The all-in-one platform will provide scientists and researchers across biotechnology and pharmaceutical companies with short term, on demand access to more than 35 petabytes of de-identified clinical and molecular datasets, along with the latest artificial intelligence analytical tools to accelerate drug discovery and development.

Clarius Introduces First Ultrasound System That Uses AI and Machine Learning to Recognize Anatomy for an Instant Window into the Body
In its biggest Clarius Ultrasound App update to date, Clarius Mobile Health (@clariusmhealth) is introducing the ability for its wireless ultrasound systems to automatically detect body anatomy being scanned by clinicians. This new feature is now available with the Clarius C3 HD multipurpose and the Clarius PA HD phased array ultrasound systems.

DataRobot Launches AI for Health Incubator
DataRobot (@DataRobot), a company in enterprise AI, announced DataRobot’s AI for Health Incubator, a new initiative that invites entrepreneurs, companies, institutions, colleges and universities, and non-profits to develop and deploy novel solutions for the health and healthcare market. DataRobot’s AI for Health Incubator, which was unveiled during DataRobot’s AI Experience Worldwide, will provide pro-bono access to the DataRobot platform and hands-on support from its customer success teams. Interested organizations can apply now through June 11.

Biobeat’s AI-Powered Remote Patient Monitoring Platform Receives A Full CE Mark
Biobeat (@BiobeatT), a wearable remote patient monitoring solutions company for the healthcare continuum, announced that its full AI-powered wearable remote patient monitoring platform has received a full CE Mark. The approval encompasses Biobeat’s wrist and chest-patch monitoring devices’ accurate and continuous monitoring of crucial patient vital signs, including blood oxygen saturation, respiratory rate, non-invasive cuffless blood pressure, pulse rate, pulse rate variability, mean arterial pressure, pulse pressure, stroke volume, cardiac output, cardiac index, systemic vascular resistance and skin temperature.

To Read

AI-Enhanced Cardiology Takes Another Step Forward – By John Halamka MD and Paul Cerrato – Asymptomatic left ventricular systolic dysfunction (ALVSD) may not be the most familiar disorder in medicine, but it nonetheless increases a patient’s risk of heart failure and death. Unfortunately, ALVSD is not that easily detected. Characterized by low ejection fraction (EF) — a measure of how much blood the heart pumps out during each contraction — it’s readily diagnosed with an echocardiogram. But because the procedure is expensive, it’s not recommended as routine screening for the general public. A recently developed AI-enhanced algorithm that’s used in conjunction with an ECG can identify low EF, one of many advances that will eventually make machine learning an essential part of every clinician’s “tool kit.”

Lessons Learned from the CMS Artificial Intelligence Health Outcomes Challenge – By Elizabeth Fowler, Ph.D., J.D., Deputy Administrator and Director of CMS’s Center for Medicare and Medicaid Innovation, and James Gerber, J.D., M.B.A., Director, Division of Portfolio Management and Strategy, CMS Innovation Center (@CMSGov) – On April 30, CMS announced the winner and runner-up of the CMS Artificial Intelligence (AI) Health Outcomes Challenge (AI Challenge), a prize competition for innovators to demonstrate how artificial intelligence tools can be used to accelerate the development of AI solutions that predict patient health events for Medicare beneficiaries for potential use by the CMS Center for Medicare and Medicaid Innovation (Innovation Center) in testing innovative payment and service delivery models. This announcement, which marked the culmination of a two-year competition, was an exciting example of how public/private partnerships can drive innovation. The AI challenge was notable for several reasons…

How AI Robotics are Transforming the Health Care Industry – By Abeer Raza, Founding Partner, ReadWrite (@RWW) – Two of the most futuristic technologies that the world is leveraging today are AI and Robotics. Implementing these two technologies can lead to innovations in several industry verticals, including the healthcare industry. AI and Robotics are already working in several healthcare establishments. They’re carrying out tasks such as genetic testing, robotic surgery, cancer research, data collection, and more.

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.