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.
Listen
From Healthcare de Jure -Tune in as we serve up the hottest healthcare issues of the day, all from a legal point of view. From public policies and Federal initiatives to privacy and security, join host Matt R. Fisher (@Matt_R_Fisher) as he and his guests discuss a smorgasbord of topics, giving hospitals, physicians, vendors and patients a seat at the table. This episode, Matt chats with Eric Sullivan, Senior Vice President Innovation and Data Strategies at Inovalon (@InovalonInc), discussing a background on artificial intelligence, testing capabilities and practical applications in healthcare.
To Read
Why Artificial intelligence is future? – Xcelance https://t.co/Ix3HGMTQka pic.twitter.com/IbF8alyg1i
— Matthew Lamons (@mlamons1) November 20, 2018
Towards Data Science
Automatic Question Answering – Querying Information from structured and unstructured data has become very important. There is a lot of textual data, FAQ, newspapers, articles, documentation, user cases, customer service requests, etc. Quite hard to keep in mind all that information. Who won the last football Euro Cup? What is Bitcoin? When is the birthday of a famous singer? To find some information, we need to search a document, spend a couple of minutes reading before you find the answer. Nazar Grycshuk, Data Scientist at Sigma Software and the author of this article, believes that automatic QnA system could save the most valuable resource in our lives — time.
#AI #Strategy starts with great questions @v_vashishta and I work with you to uncover the value, build and execute the plan.#Data #Science #Deep #Learning #Strategy #Product #Design & #Implementation https://t.co/uIuY7SAUhQ
— Matthew Lamons (@mlamons1) November 19, 2018
In the News
DrChrono Teams up with Diagnoss to Help Practices Improve Medical Coding Through Artificial Intelligence Technology
DrChrono Inc. (@drchrono), the company enabling the medical practice of the future, and Diagnoss, the company focused on reducing the administrative burden of medical practices, have partnered together to offer physician practices AI technology to help automate the medical coding process.
Life Image and Mendel.ai Partner to Bring the Power of AI to Accelerate Clinical Trial Process for Life Sciences and Academic Medical Facilities
Life Image (@lifeimageinc), the world’s largest global network for sharing clinical and imaging data that is powered by industry leading interoperability standards, and Mendel.ai (@MendelHealth), an AI engine that uses deep learning to match patients with clinical treatment options for cancer, announced a new strategic partnership that will facilitate the adoption and enhancement of AI in oncology site selection and patient recruitment.
Arterys Introduces First Complete AI- and Cloud-powered Solution for Most Challenging Medical Imaging Analysis Workflow
Arterys (@ArterysInc), the leader in intelligent, cloud-based medical imaging software, has introduced more than 80 enhancements to its Cardio AIMR solution, which combines the power of deep learning and cloud computing to automate analysis of cardiac MR images. With these additions, Arterys Cardio AIMR is the first and only commercial solution to offer deep learning-based perfusion* and delayed enhancement analysis*. The new features also improve clinician workflow, streamlining and speeding analysis with automated and easily editable ventricular volume measurements.
Events
GA HIMSS Lunch & Learn
When: November 29th, 2018 11:30-1:00 pm ET
Where: Maggiano – Buckhead, Atlanta GA
Artificial Intelligence and The Healthcare of Tomorrow – AI technologies are opening the promise of enhanced clinical decision support, which can improve the way we care for patients, as well as reduce the cost of care. Today, AI is able to provide insights in population health, act as a virtual assistant, and outperform humans in object detection and classification for diagnostic purposes. Join their panel of healthcare providers and industry experts as they attempt to separate hype from the real world of AI, share clinical success stories, lessons learned, and discuss present and future challenges that this new frontier offers.
AI Solve: Healthcare – Webcast Replay
Recorded March 21, 2018 at UCSF in SanFrancisco
View the recording
AI is already beginning to shape the healthcare industry, Intel brought together some of the leading minds in the space. At the event called Intel SOLVE: Healthcare, in San Francisco, Intel brought together researchers from Harvard, Princeton, Stanford, GE Healthcare, Optum, Mayo Clinic, The MIT/Harvard Broad Institute and more to talk about the work they are doing with AI.
To Follow
- Patrick Grossmann @GrossmannPat
- Steven Astorino @astorino_steven
- AI Healthcare News @AIHealthNews
- Mirada Medical @MiradaMedical
- IBM Watson Health @IBMWatsonHealth
- CrossChx @CrossChx
- Dr. Eric Topol @EricTopol
- Dr. Marc Chasin @M_Chasin
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:
- Natural Language Processing to enable it to communicate successfully in English
- Knowledge Representation to store what it knows or hears
- Automated Reasoning to use the stored information to answer questions and to draw new conclusions
- Machine Learning to adapt to new circumstances and to detect and extrapolate patterns
- Computer Vision to perceive objects
- 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.