artificial intelligence (AI)

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It's 2019. Smartphones are Out...On to the Next Big Thing...

It's amusing to watch old movies where plot points often involved someone's inability to talk to the person they needed, in the pre-mobile phone era. We take our smartphone's omnipresence and virtual omnipotence as a given in our daily lives and treat even its temporary loss as a major inconvenience. So why are people already wondering if the smartphone era is almost over? Speculation on this is not new (voice has been touted as the next big platform for years), but intensified after Apple announced reduced revenue expectations earlier this year -- the first time in 16 years. It specifically cited slower iPhone sales in China and, even more jarring, said it would no longer break out unit sales of iPhones...

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John Koenig

John Koenig is a data scientist based in the Washington DC area who specializes in designing custom machine learning and artificial intelligence algorithms for large-scale clients in the healthcare industry. He is currently the senior data scientist for a Department of Health and Human Services program that is using AI and blockchain technologies to optimize federal procurement. Read More »

Lebanon Should Not Miss Out On The Next Big Technological Advance: Mechatronics

Barbar Akle | Executive Magazine | December 11, 2014

...Currently, the field of automation and robotics is experiencing rapid developments due to the accelerated progress of artificial intelligence, computer vision, micromanufacturing and rapid prototyping. This means that complex and intelligent machines will start replacing some jobs, while also providing convenience and personal assistance...

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Leveraging Artificial Intelligence in Search and Rescue Operations

Press Release | Perdue University | May 1, 2019

Rescue teams descended on the destruction left by Hurricane Michael in October, frantically searching for survivors. But a week later, more than 1,000 people were still not accounted for, leaving families to wait and hope.Drone assistance in natural disaster response now is simplistic at best with a number of hurdles. But new research led by Purdue University professors is working to use artificial intelligence and learning algorithms to create a platform allowing multiple drones to communicate and adapt as mission factors change.

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Leveraging the "Learning Health Community" Concept in Education

This idea of an iterative engaged learning environment (we can call it a “Learning Health Community”) is not far-fetched. Such a system would require quality evidence-based data and information delivered in real-time based on the real-world experiences of millions of patients. As new verified information and data develop, these would be incorporated and then deployed. We would harness the power of existing and future knowledge in a form that is usable by both medical professionals and the patients they serve. The questioning fathers and others similarly situated could access the Internet for augmented and personalized health information.

Machine Learning in Healthcare: Part 1 - Learn the Basics

This article is the first in a three-part series that will discuss how machine learning impacts healthcare. The first article will be an overview defining machine learning and explaining how it fits into the larger fields of data science and artificial intelligence. The second article will discuss machine learning tools available to the average healthcare worker. The third article will use a common open source machine learning software application to analyze a healthcare spreadsheet. Part I was written to help healthcare workers understand the fundamentals of machine learning and to make them aware that there are simple and affordable programs available that do not require programming skills or mathematics background...

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Machine Learning in Healthcare: Part 3 - Time for a Hands-On Test

Every inpatient and outpatient EHR could theoretically be integrated with a machine learning platform to generate predictions, in order to alert clinicians about important events such as sepsis, pulmonary emboli, etc. This approach may become essential when genetic information is also included in the EHR which would mandate more advanced computation. However, using machine learning and artificial intelligence (AI) in every EHR will be a significant undertaking because not only do subject matter experts and data scientists need to create and validate the models, they must be re-tested over time and tested in a variety of patient populations. Models could change over time and might not work well in every healthcare system. Moreover, the predictive performance must be clinically, and not just statistically significant, otherwise, they will be another source of “alert fatigue.”

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Make No Little Plans

Ever seen the new TV show 'Pure Genius'?  Probably not; its ratings are dismal.  I've seen it, and, well, it isn't very good.  But what I like is the premise: a young tech billionaire builds a hospital using only the latest technology, and treats patients regardless of cost. Gotta give the creators props for trying to re-imagine hospitals.  The health care industry could do with some serious attempts at re-imaging, and not just for hospitals. What made me think about this were two stories about the auto industry, which is desperately trying to remain relevant in a world of Uber, self-driving cars, and our love affair with our various digital devices...

Many Healthcare Technologies Are Married to the Fee-for-Service Model

Juliet Preston | MedCity News | January 10, 2017

Monday’s 5 p.m. digital health panel at the J.P. Morgan Healthcare Conference happened to coincide with a presentation given by the popular U.S. Vice President Joe Biden. Some attendees were torn. For those that did make it, panel moderator Bob Kocher promised some topical debates far more interesting than that “moon-thing” Biden has been up to. It was all of the fun, without the metal detectors. A partner at Venrock Ventures, Bob Kocher set the stage with some fundamental observations about how technology can help enhance healthcare for all stakeholders...

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Microsoft and Partners Combine the Cloud, AI, Research and Industry Expertise to Focus on Transforming Health Care

Peter Lee | Microsoft Blog | February 16, 2017

...Healthcare NExT, a new initiative to dramatically transform health care, will deeply integrate greenfield research and health technology product development, as well as establish a new model at Microsoft for strategic health industry partnerships. Through these collaborations between health care partners and Microsoft’s AI and Research organization, our goal is to enable a new wave of innovation and impact using Microsoft’s deep AI expertise and global-scale cloud.This initiative includes investments in resources for our partners to capture new opportunities to apply AI to healthcare, such as the Microsoft AI in Health Partner Alliance, an expanding group of partners focused on advancing health technology. Alliance members will receive unique training and access to Microsoft technologies, engineering expertise and data sets. Read More »

Microsoft, Amazon, Google, IBM, Oracle, and Salesforce Issue Joint Statement Making Commitment to Open Source Healthcare Interoperability

Josh Mandel | Microsoft Industry Blog | August 13, 2018

Interoperability is an overlapping set of technical and policy challenges, from data access to common data models to information exchange to workflow integration – and these challenges often pose a barrier to healthcare innovation. Microsoft has been engaged for many years on developing best practices for interoperability across industries. Today, as health IT community leaders get together at the CMS Blue Button 2.0 Developer Conference here in Washington, DC, we’re pleased to announce that Microsoft has joined with Amazon, Google, IBM, Oracle, and Salesforce in support of healthcare interoperability...

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My Phone Says I've Looked Better

Current AI can sift through millions of photos to pick you out of a crowd, with varying degrees of success.  Camera angles, make-up, hats, quality of image all factor into how successful such software is.  Given the recent rapid rates of improvement, though, these are bumps in the road, not insurmountable barriers. Other software can process your facial expressions, allowing them to make some good guesses about your emotions.  If you are a marketer, or a law enforcement officer, this information might be gold, but if your privacy is important, it might be a scary invasion.  Someone is always watching. What I want to know is when this AI can tell if I look sick.

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New Report: Top Challenges Facing HHS Includes Harnessing Data

In November 2019 the US Department of Health and Human Services (HHS) Office of Inspector General (OIG) released a new report, Top Management and Performance Challenges Facing HHS. Divided into six major sections, this report reviews the OIG's observations with respect to financial integrity of HHS programs, value and quality, protecting the health and safety of beneficiaries as well as the public at large, harnessing data to achieve these goals, and working across government. The fifth challenge, "Harnessing Data To Improve Health and Well-Being of Individuals," is particularly foundational. Read More »

New Study: 'Cloud Of Things' Could Make Customer Service Better, Humanity Worse

Adrienne Lafrance | The Atlantic | May 14, 2014

Experts predict technology will improve daily transactions by 2025, but there are major caveats...

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New Trends and Troubles for AI in Medicine

Nelson Williams | Silicon Angle | March 11, 2017

Medicine is a complex field. So complex that any given person can’t know more than a fraction of what’s going on. Keeping up with the latest discoveries is impossible. Machine learning and other forms of artificial intelligence offer a new way of looking at medicine and a great power to automate medical tasks. At the South by Southwest conference event in Austin, TX, a panel of experts came together to discuss the state of medical AI and how machine learning can benefit both patients and doctors...

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