Length of Stay (LOS) is a critical factor in managing hospital quality & economic outcomes in Healthcare. The metric is calculated by summing the total number of days for all discharges & dividing it by the total number of discharges. Insurance programs such as Medicare are moving to a model where they are compensating Hospitals the same amount for a specific surgery (e.g. Joint replacement) regardless of the number of days spent in the hospital. Therefore, hospitals & the overall healthcare ecosystem are motivated to reduce LOS.

The White House has issued a sequel to its October report on how the U.S. should approach artificial intelligence and its effects on various groups and institutions. Today's report focuses on the potential economic effects of AI, and while it's far from a dark outlook, it does warn that with improper handling, automation could drive further inequality in this already deeply divided country. "You look at the last couple decades, we have seen an increase in inequality," said Jason Furman, Chairman of the Council of Economic Advisers, on a press call discussing the paper. "In part that increase has been because of a technological fact: that technological innovation, more recently, has helped complement people with higher skills. So we now have a few decades of experience with technology helping to contribute to inequality."

Meet YoloData, one of the latest DMV-area data analytics startups promising to make sense of millennials for businesses. The Ashburn, Va.-based startup provides data scientists and business developers with an aggregated data platform focused on how millennials might respond to a business. Co-founder and CEO Bryan Short said the platform collects financial and health data, mostly, from public government sources and a few private partnerships, but it also lets customers import their own private data for individual analysis. In January, the nine-month-old company will close its first round of $500,000 backed mostly by local angel investors who have previously invested in Short's previous ventures, including a few mobile apps. This raise will be used to prep YoloData's technology for beta testing in the spring.

On Tuesday, the US government continued a national conversation on the impact of artificial intelligence on the workforce. The new White House report, Artificial Intelligence, Automation, and the Economy, serves as a follow-up to its October report, Preparing for the Future of Artificial Intelligence, which looked at the role of government in the development and implementation of artificial intelligence. It's an effort by the US government to address the huge impact automation is currently having on jobs--which promises to be felt more deeply as artificial intelligence advances. The report explores the history and impact of automation on the economy, and looks at jobs that could be lost or gained from artificial intelligence. It also outlines three policy strategies meant to help prevent automation from taking jobs away from humans.

Why is it important to democratize machine learning? Why is it important to democratize machine learning? For two reasons: first, because machine learning and artificial intelligence have tremendous potential for value creation, and we should not let any of that potential go to waste. People with the drive and intelligence required to advance the field of ML or to use AI to create great things can come from anywhere, and we have a responsibility to make sure that these people can readily access the knowledge and tools they will need to realize their full potential. What's more, we should do our best to inspire capable people the world over so that they will want to dedicate their talents to value creation through AI.

Artificial Intelligence (AI) is rapidly becoming the biggest issue on the agenda for many businesses. The current speed of development, the sheer range of possible applications, and the potential impact of AI suggest that it's time for CEOs to pay attention. So, what are the questions every CEO should be asking? Futurist Rohit Talwar, CEO of Fast Future Publishing believes there are ten questions that need to be asked in order to assess and invest in AI's transformative potential: 1. AI will change the philosophy, practice and management of business. It is beginning to transform businesses and replace even senior management and leadership roles.

DeLiang Wang was in college when his mother began to lose her hearing in the 1980s. Today, she struggles to listen to and participate in a conversation, even with her hearing aids. Dinners with her large family are frustrating and, often, exhausting. At 91, she is "essentially deaf," Wang said, because her hearing aids provide so little benefit that she seldom wears them. So Wang, now a professor computer science and engineering at Ohio State University, is building a better hearing aid, with some help from GPUs and deep learning.

Despite some significant arrivals, 2016 also failed to deliver some long-awaited technologies. And some of what we eagerly ripped the wrapping paper off proved to be a letdown. Here's a rundown of the gifts IT didn't get in 2016. If you want to print out a stand for your phone or a model for a new product, you can easily find a 3D printer for the office that can do that -- as long as you want to print them out in plastic. You can spend more and get a 3D printer that can UV cure resin and make small objects like custom-fit earplugs in about 10 minutes (I watched my ACS Custom in-ear monitor headphones get printed from digital scans of my ear canals earlier this year). Even HP's $140,000 Multi Jet Fusion printers -- promised for this year and offering multi-color printing -- only just went on sale, and they still only print nylon.

December 27, 2016 --Apple, a company known for their secrecy, announced at a conference earlier this month that their artificial intelligence (AI) team would begin publishing research papers. The announcement, made during a presentation via a single slide at the Neural Information Processing Systems (NIPS) conference, meant that the tech giant would begin engaging with the rest of the AI research community; a community that has long been combining efforts to further develop AI technology. In fact, for some time Facebook, Amazon, Microsoft, Google, and IBM – companies that could benefit greatly from artificial intelligence – have all been openly sharing their research in an effort to jointly progress in this nascent industry. And now, less than a month after announcing their new policy, Apple has already published their first research paper, titled "Learning from Simulated and Unsupervised Images through Adversarial Training". The paper addresses intelligent image-recognition technology, which involves training machines to recognize objects using computer-generated images.

Healthcare organizations interested in engaging in the world of semantic computing may be able to do with less effort and lower costs as the Machine Learning-as-a-Service (MLaaS) market grows from $480 million in 2015 to nearly $5.4 billion by 2022. With a predicted compound annual growth rate of 41.2 percent, the MLaaS market may help providers access the natural language processing and artificial intelligence tools becoming increasingly important for advanced big data analytics, risk stratification, consumer engagement, and value-based care. The report by Statistics MRC identifies healthcare as an industry where machine learning is likely to take root, furthered by growing interest in the Internet of Things, cloud computing, and the need to drastically improve consumer relationships. Tight organizational budgets and limited talent pools will likely drive providers to engage third-party "as a service" partners across a number of infrastructure areas. Healthcare organizations are likely to look for customized solutions that adhere to the strict privacy and security requirements that structure the healthcare landscape.