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 (@drnic1) talks to Won Chung MD. The discussion offers great insights around correlation with car model, marriage and beyond for health prediction. Linking our buying and social data to outcomes and then offering this for better interventions.
— Oliver Wyman Health (@OWHealthEditor) October 22, 2018
A Piedmont Hospital case study, written by Health Catalyst
Artificial Intelligence Improves Accuracy of Heart Failure Readmission Risk Predictions – To improve the accuracy and timeliness of its risk prediction model, MultiCare and Pulse Heart partnered with Health Catalyst, leveraging the Health Catalyst® Analytics Platform and catalyst.ai™ to develop a HF 30-day readmission risk-prediction model that utilizes MultiCare’s historical data to determine the probability of currently admitted patients being readmitted within 30-days of discharge.
— Medtronic (@Medtronic) October 1, 2018
World Economic Forum
7 amazing ways artificial intelligence is used in healthcare – One of the biggest impacts of new technology – and perhaps the most life-changing – will be felt in healthcare. Diagnosis of illness will be fast and efficient, and medicine will be highly personalised. Wearable technology will be the norm, and we’ll know we are sick before we even get a single symptom. Meanwhile, new drugs will come to market at breakneck speed as clinical trials get faster and more accurate. Ultimately, we will become our own doctors.
In the News
— Matthew Lamons (@mlamons1) October 23, 2018
WhiteHatAI Announces Artificial Intelligence Driven Healthcare Payment Integrity Platform
An innovative healthcare AI software company, WhiteHatAI (@WhiteHatAI) announced the release of the Centaur Software platform for detecting Fraud, Waste, and Abuse in healthcare transactions.
Orion Health launches Amadeus CORE to help healthcare sector leverage data analytics and machine learning
Orion Health (@OrionHealth) announced Amadeus CORE, the latest in its suite of data management, storage and sharing solutions to enable healthcare organizations to take a first step in their data journey towards harnessing the power of big data. With vast amounts of data from multiple sources to contend with, healthcare organizations struggle to deal with the complicated and expensive technology options for storing large volumes of data securely.
ProMedica Health System to Deploy PeriGen Artificial Intelligence Solution Focused on Improving Outcomes in Childbirth
PeriGen (@PeriGen), an innovator of perinatal early warning systems, announced that ProMedica (@ProMedicaHealth), a not-for-profit integrated health care organization serving 30 states, plans to deploy the company’s PeriWatch™ Vigilance™, an artificial intelligence-based maternal-fetal early warning system (EWS), in all of its labor and delivery hospitals. Vigilance is designed to help clinicians identify troubling trends earlier and more consistently than manual assessments and creates a common language for nurses and physicians to assess cases.
Held September 30-October 2, 2018
PATH Summit Pictureshttps://t.co/YMPdQb8V9t
— PATH Health (@PATHHealthAI) October 1, 2018
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.
- 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.