machine learning

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Apixio Illuminates The Pain of Recording Patient Risk Factors (Part 1)

Andy Oram | EMR & HIPPA | October 27, 2016

Many of us strain against the bonds of tradition in our workplace, harboring a secret dream that the industry could start afresh, streamlined and free of hampering traditions. But history weighs on nearly every field, including my own (publishing) and the one I cover in this blog (health care). Applying technology in such a field often involves the legerdemain of extracting new value from the imperfect records and processes with deep roots. Along these lines, when Apixio aimed machine learning and data analytics at health care, they unveiled a business model based on measuring risk more accurately so that Medicare Advantage payments to health care payers and providers reflect their patient populations more appropriately...

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12 Open Source Tools for Natural Language Processing

Natural language processing (NLP), the technology that powers all the chatbots, voice assistants, predictive text, and other speech/text applications that permeate our lives, has evolved significantly in the last few years. There are a wide variety of open source NLP tools out there, so I decided to survey the landscape to help you plan your next voice- or text-based application. For this review, I focused on tools that use languages I'm familiar with, even though I'm not familiar with all the tools. (I didn't find a great selection of tools in the languages I'm not familiar with anyway.) That said, I excluded tools in three languages I am familiar with, for various reasons.

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9 Resources for Data Science Projects

Data science, machine learning, artificial intelligence, and deep neural nets are all hot topics these days (and key terms that might help this post with some SEO, unless the AI sees through my attempts). Below I've shared several of the resources I use regularly while working on data science projects over the last few years. I don't read many books, so that I've shared even one is evidence of how important it is. There are enough resources here to get even the most novice engineer started on a path towards data science mastery in this new age where data science skills will be needed at every level. There is a tool for performing the work, a class taught by a renowned Stanford professor, websites with tutorials to give you real-life experience, and a site dedicated to making the latest research available to all for free so you can learn more if you want.

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A Tour of Google's 2016 Open Source Releases

Open source software enables Google to build things quickly and efficiently without reinventing the wheel, allowing us to focus on solving new problems. We stand on the shoulders of giants, and we know it. This is why we support open source and make it easy for Googlers to release the projects they're working on internally as open source. We've released more than 20-million lines of open source code to date, including projects such as Android, Angular, Chromium, Kubernetes, and TensorFlow. Our releases also include many projects you may not be familiar with, such as Cartographer, Omnitone, and Yeoman...

ApacheCon 2020 features Natural Language Processing for Electronic Medical Records in dedicated track on Apache cTAKES

Press Release | Apache Software Foundation | September 21, 2020

ApacheCon, the official conference series of The Apache Software Foundation (ASF), the world's largest Open Source foundation, announced today its first dedicated track on Apache cTAKES. The track will be held on all three days of the ApacheCon@Home virtual conference, taking place online 29 September - 1 October 2020. Registration is free of charge for all participants and is required in advance to participate. Now in its 22nd year, ApacheCon is the primary gathering of the collective Apache community worldwide, drawing attendees from more than 130 countries. ApacheCon showcases the latest breakthroughs from dozens of Apache projects, upcoming innovations in the Apache Incubator, and sessions on developing community-led Open Source projects "The Apache Way".

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Artificial Intelligence and Machine Learning Bias has Dangerous Implications

Algorithms are everywhere in our world, and so is bias. From social media news feeds to streaming service recommendations to online shopping, computer algorithms—specifically, machine learning algorithms—have permeated our day-to-day world. As for bias, we need only examine the 2016 American election to understand how deeply—both implicitly and explicitly—it permeates our society as well. What’s often overlooked, however, is the intersection between these two: bias in computer algorithms themselves. Contrary to what many of us might think, technology is not objective...

Artificial intelligence in medicine: Is the genie out of the bottle?

It is probably a given that artificial intelligence (AI) will become an integral part of healthcare delivery and of our public health infrastructure. What is not a given is that we will easily reach that point, and maintain progress in a way that maximizes its effectiveness in achieving the goals we have come to expect of it – efficient and improved healthcare and public health systems. In other words, making the health of people better in a cost-effective way. Responsible commentators have already begun to question the value of AI in medicine.

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Artificial Intelligence Is Not as Smart as You (or Elon Musk) Think

Ron Miller | Tech Crunch | July 25, 2017

In March 2016, DeepMind’s AlphaGo beat Lee Sedol, who at the time was the best human Go player in the world. It represented one of those defining technological moments like IBM’s Deep Blue beating chess champion Garry Kasparov, or even IBM Watson beating the world’s greatest Jeopardy! champions in 2011. Yet these victories, as mind-blowing as they seemed to be, were more about training algorithms and using brute-force computational strength than any real intelligence...

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Black Duck Forms Security Advisory Board, Adds Research and Data-Mining Group

Press Release | Black Duck | May 5, 2016

Black Duck...today announced strategic initiatives to add security expertise and strengthen its research and innovation capabilities. The company has created a five-member Security Advisory Board comprising experienced security executives, and has launched Black Duck Research, a Vancouver-based, applied-research group focused on data mining, machine learning, natural language processing, big data management and analytics, and software quality...

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Can Data Provide the Trust we Need in Health Care?

One of the problems dragging down the US health care system is that nobody trusts one another. Most of us, as individuals, place faith in our personal health care providers, which may or may not be warranted. But on a larger scale we’re all suspicious of each other... Read More »

Christine Doig on Data Science as a Team Discipline

Srini Penchikala | Info Q | August 26, 2016

Data science is about the design and development of solutions to extract insights from data (structured and unstructured) using machine learning and predictive analytics techniques and tools. Data Science as a discipline and Data Scientist as a role have been getting lots of attention in the recent years to solve real world problems with solutions ranging from fraud detection to recommendation engines. Christine Doig, Senior Data Scientist at Continuum Analytics, spoke at this year’s OSCON Conference about data science as a team discipline and how to navigate the data science Python ecosystem.

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Cloudera Unveils Open Source Workbench to Accelerate Data Science and Machine Learning

Press Release | Cloudera | May 1, 2017

Cloudera, Inc., the provider of the leading modern platform for machine learning and advanced analytics built on the latest open source technologies, announced the general availability of the Cloudera Data Science Workbench, its self-service tool for data scientists. The workbench, announced in beta at Strata+Hadoop World San Jose 2017, enables fast, easy and secure self-service data science for the enterprise. "We are entering the golden age of machine learning and it's all about the data. However, data scientists continue to struggle to build and test new analytics projects as fast as they would like, particularly in large scale environments," said Charles Zedlewski, senior vice president, Products at Cloudera.

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Coopetition: All's Fair in Love and Open Source

PostgreSQL vs. MySQL. MongoDB vs. Cassandra. Solr vs. Elasticsearch. ReactJS vs. AngularJS. If you have an open source project that you are passionate about, chances are a competing project exists and is doing similar things, with users as passionate as yours. Despite the "we're all happily sharing our code" vibe that many individuals in open source love to project, open source business, like any other, is filled with competition. Unlike other business models, however, open source presents unique challenges and opportunities when it comes to competition...

Crowdsourcing a Better Prostate Cancer Prediction Tool

Press Release | University of Colorado Anschutz Medical Campus | November 15, 2016

Knowing the likely course of cancer can influence treatment decisions. Now a new prediction model published today in Lancet Oncology offers a more accurate prognosis for a patient's metastatic castration-resistant prostate cancer. The approach was as novel as the result - while researchers commonly work in small groups, intentionally isolating their data, the current study embraces the call in Joe Biden's "Cancer Moonshot" to open their question and their data, collecting previously published clinical trial data and calling for worldwide collaboration to evaluate its predictive power...

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Data Breaches Through Wearables Put Target Squarely on IoT in 2017

Ryan Francis | Java World | January 3, 2017

Security needs to be baked into IoT devices for there to be any chance of halting a DDoS attack, according to security experts. Read More »