artificial intelligence (AI)

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Interoperability As A Service (IAAS): The AI Enabled Blockchain

Edward Bukstel | LinkedIn | April 18, 2017

It’s time for patients to come to terms with the fact that there is no financial incentive for healthcare providers to consolidate and normalize data from disparate providers. Patients must be cautious maintaining their patient records on a blockchain or another platform that cannot be used by other institutions, providers, or entities. Without portability, blockchains will add little value to advance patient medical record mobility. Healthcare providers may discover some indirect benefits from the consolidation of medical records — even records not immediately accessible by patients...

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Interview with Stefano Maffulli First Executive Director of the Open Source Initiative

The Open Source Initiative has served as the key steward of open source software since its formation in 1998. In September 2021, the Open Source Initiative board hired Stefano Maffulli as its first Executive Director. I recently interviewed Stefano to learn more about him and his vision for the Open Source Initiative.

Introducing OpenAI

Greg Brockman, Ilya Sutskever, and the OpenAI team | OpenAI blog | December 11, 2015

OpenAI is a non-profit artificial intelligence research company. Our goal is to advance digital intelligence in the way that is most likely to benefit humanity as a whole, unconstrained by a need to generate financial return. Since our research is free from financial obligations, we can better focus on a positive human impact. We believe AI should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible.The outcome of this venture is uncertain and the work is difficult, but we believe the goal and the structure are right. We hope this is what matters most to the best in the field.

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Irvine, Calif-Based Health Tech Firm Acquires Growth Strategy Funding for NICU Mobile App

Press Release | Rapid Healthcare, Inc. | November 17, 2016

Rapid Healthcare Inc., a mobile medical apps software company based in Irvine, California, is proud to announce an important alliance that will increase growth strategies for improved access to health care professionals through funding provided by Watermark Venture Capital. Watermark is a privately held California firm currently deploying its services to support large national companies to start-ups. Watermark Venture Capital selects award candidates for capital infusion, based in key technology growth areas such as the healthcare, artificial intelligence, SaaS and more...

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Is China Already in the 21st Century in the Fields of AI for Healthcare and Quantum Computing?

It is 2018 everywhere, but not every country is treating being in the 21st century equally. China is rushing into it, even in healthcare, while the United States is tip-toeing its way towards the future. Especially in healthcare. Ready or not, the future is here...and the U.S. may not be ready...Artificial Intelligence: Yes, the U.S. has been the leader in A.I., with some of the leading universities and tech companies working on it. That may not be enough. A year ago China announced that it intended to be the world leader in A.I. by 2025. The Next Web recently concluded that China's progress since then "remains unchecked." China is far outspending the U.S. on A.I. research and infrastructure, coordinating efforts between government, research institutes, universities, and private companies. Dr. Steven White, a professor at China's Tsinghua University, "likens the country's succeed at all costs AI program to Russia's Sputnik moment." We have yet to have that wake-up call...

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Is It Time to Purchase Your Own Quantum Computer?

I want to talk about quantum computing – and why healthcare needs to looking ahead to it. Let’s start with this: for the low, low price of $5,000, you could have your very own quantum computer.  Spin Q Technology, a Chinese company, has recently introduced its Spin Q, a less expensive, less powerful version of its Spin Q Gemini, which went for $50,000.  Other quantum computers, such as those by Google, IBM, or D-Wave, have a few more zeroes in their price.  Spin Q Technology has a clear goal in offering this version:We believe that low-cost portable quantum computer products will facilitate hands-on experience for teaching quantum computing at all levels, well-prepare younger generations of students and researchers for the future of quantum technologies."

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Is Machine Learning for the Birds?

Cacophony Project uses the latest technology to monitor and protect endangered bird populations against predators. The Cacophony Project's broad vision is to bring back New Zealand's native birds using the latest technology to monitor bird populations and humanely eliminate the introduced predators that are endangering them. The project started in our founder's backyard to measure the effectiveness of his efforts to protect the birds on his property. From this simple beginning, the project has quickly grown into a system that includes two edge devices, a cloud server, and automatic identification of animals using machine learning. The project has been completely open source from the beginning and sees regular contributions from a wide variety of volunteers.

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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 »

King's College Accelerates Synthetic Brain 3D Image Creation Using Open Source AI Models and Software Powered by Cambridge-1 Supercomputer

Press Release | King’s College London | July 26, 2021

King College London, along with partner hospitals and university collaborators, unveiled new details today about one of the first projects on Cambridge-1, the United Kingdom's most powerful supercomputer. The Synthetic Brain Project is focused on building deep learning models that can synthesize artificial 3D MRI images of human brains. These models can help scientists understand what a human brain looks like across a variety of ages, genders, and diseases. The AI models were developed by King's and NVIDIA data scientists and engineers as part of The London Medical Imaging & AI Centre for Value Based Healthcare research funded by UK Research and Innovation and a Wellcome Flagship Programme (in collaboration with University College London).

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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.

Low-cost Aplication Platforms (LCAP): What They Should Mean to Public Health

Agency budgets continue to run tight, while the demands for data modernization continue to escalate. We are also seeing weakening markets – not strengthening markets – for core public health software systems like Immunization Information Systems (IIS) and Disease Surveillance/case management systems. One of the emerging, promising approaches are Low-cost Application Platforms (LCAP). What exactly are they, where did they come from, and are they a useful strategy for developing core public health applications?

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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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