19 February 2018

How to Watch Free Live TV on Android TV


watch-free-live-tv

The number of quality programs on cable TV has declined dramatically in recent years. Global stalwarts like the BBC are still churning out incredible documentaries at a phenomenal rate, but the overall standard has unquestionably deteriorated. Perhaps that’s why cordcutting has become so popular. However, even if you hate modern TV and you’re an experienced cord cutter, there will still be times when you want to indulge in a spot of mindless channel hopping. And if you bought an Android TV device as part of your cord-cutting strategy, you’re in luck. It’s possible to enjoy legal, live TV on your...

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Assessing Cardiovascular Risk Factors with Computer Vision




Heart attacks, strokes and other cardiovascular (CV) diseases continue to be among the top public health issues. Assessing this risk is critical first step toward reducing the likelihood that a patient suffers a CV event in the future. To do this assessment, doctors take into account a variety of risk factors — some genetic (like age and sex), some with lifestyle components (like smoking and blood pressure). While most of these factors can be obtained by simply asking the patient, others factors, like cholesterol, require a blood draw. Doctors also take into account whether or not a patient has another disease, such as diabetes, which is associated with significantly increased risk of CV events.

Recently, we’ve seen many examples [1–4] of how deep learning techniques can help to increase the accuracy of diagnoses for medical imaging, especially for diabetic eye disease. In “Prediction of Cardiovascular Risk Factors from Retinal Fundus Photographs via Deep Learning”, published in Nature Biomedical Engineering, we show that in addition to detecting eye disease, images of the eye can very accurately predict other indicators of CV health. This discovery is particularly exciting because it suggests we might discover even more ways to diagnose health issues from retinal images.

Using deep learning algorithms trained on data from 284,335 patients, we were able to predict CV risk factors from retinal images with surprisingly high accuracy for patients from two independent datasets of 12,026 and 999 patients. For example, our algorithm could distinguish the retinal images of a smoker from that of a non-smoker 71% of the time. In addition, while doctors can typically distinguish between the retinal images of patients with severe high blood pressure and normal patients, our algorithm could go further to predict the systolic blood pressure within 11 mmHg on average for patients overall, including those with and without high blood pressure.
LEFT: image of the back of the eye showing the macula (dark spot in the middle), optic disc (bright spot at the right), and blood vessels (dark red lines arcing out from the bright spot on the right). RIGHT: retinal image in gray, with the pixels used by the deep learning algorithm to make predictions about the blood pressure highlighted in shades of green (heatmap). We found that each CV risk factor prediction uses a distinct pattern, such as blood vessels for blood pressure, and optic disc for other predictions.
In addition to predicting the various risk factors (age, gender, smoking, blood pressure, etc) from retinal images, our algorithm was fairly accurate at predicting the risk of a CV event directly. Our algorithm used the entire image to quantify the association between the image and the risk of heart attack or stroke. Given the retinal image of one patient who (up to 5 years) later experienced a major CV event (such as a heart attack) and the image of another patient who did not, our algorithm could pick out the patient who had the CV event 70% of the time. This performance approaches the accuracy of other CV risk calculators that require a blood draw to measure cholesterol.

More importantly, we opened the “black box” by using attention techniques to look at how the algorithm was making its prediction. These techniques allow us to generate a heatmap that shows which pixels were the most important for a predicting a specific CV risk factor. For example, the algorithm paid more attention to blood vessels for making predictions about blood pressure, as shown in the image above. Explaining how the algorithm is making its prediction gives doctor more confidence in the algorithm itself. In addition, this technique could help generate hypotheses for future scientific investigations into CV risk and the retina.

At the broadest level, we are excited about this work because it may represent a new method of scientific discovery. Traditionally, medical discoveries are often made through a sophisticated form of guess and test — making hypotheses from observations and then designing and running experiments to test the hypotheses. However, with medical images, observing and quantifying associations can be difficult because of the wide variety of features, patterns, colors, values and shapes that are present in real images. Our approach uses deep learning to draw connections between changes in the human anatomy and disease, akin to how doctors learn to associate signs and symptoms with the diagnosis of a new disease. This could help scientists generate more targeted hypotheses and drive a wide range of future research.

With these promising results, a lot of scientific work remains. Our dataset had many images labeled with smoking status, systolic blood pressure, age, gender and other variables, but it only had a few hundred examples of CV events. We look forward to developing and testing our algorithm on larger and more comprehensive datasets. To make this useful for patients, we will be seeking to understand the effects of interventions such as lifestyle changes or medications on our risk predictions and we will be generating new hypotheses and theories to test.


References

[1] Gulshan, V. et al. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA 316, 2402–2410 (2016).

[2] Ting, D. S. W. et al. Development and Validation of a Deep Learning System for Diabetic Retinopathy and Related Eye Diseases Using Retinal Images From Multiethnic Populations With Diabetes. JAMA 318, 2211–2223 (2017).

[3] Esteva, A. et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature (2017). doi:10.1038/nature21056

[4] Ehteshami Bejnordi, B. et al. Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer. JAMA 318, 2199–2210 (2017).


USB Over Ethernet: The Most Powerful System You Aren’t Using


usb-over-ethernet

The USB port on your computer is invaluable. It connects your computer to almost every other important device. The internet is also invaluable. It connects your computer to any other in the world. Combine the two and USB over Ethernet is an incredibly powerful system you haven’t been using. This isn’t the same as one of those USB-to-Ethernet adapters, by the way, which convert your USB ports into plugs for Ethernet cables. What Is USB Over Ethernet? USB over Ethernet (also called USB over Network or USB over IP) is a system to share USB-based devices over Ethernet, Wi-Fi, or...

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Kidtech startup SuperAwesome is now valued at $100+ million and profitable


 Technology companies like Facebook and Google are scrambling to catch up to the fact that the kids have joined a web originally built for adults, and are using it the way adults do – by liking and commenting, sharing, clicking through on personalized recommendations, and viewing ads. But the technology underpinning apps and sites built for kids can’t operate the same way as it does… Read More
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Facebook will verify the location of US election ad buyers by mailing them postcards


 Facebook’s global director of policy programs says it will start sending postcards by snail mail to verify buyers of ads related to U.S. elections. Katie Harbath, who described the plan at a conference held by the National Association of Secretaries of State, didn’t reveal when the program will start, but told Reuters it would be before the congressional midterm elections in November. Read More
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Twitter Kills its Desktop App for Mac Users


Twitter for Mac is no more. Twitter has already pulled the app from Apple’s App Store, and will end support completely on March 18, 2018. There are obviously other third-party apps available, but Twitter is directing Mac users to start using Twitter on the web instead. The world is slowly but surely moving away from desktop applications. Which is ironic given that apps are what makes everyone’s smartphones tick. However, this change isn’t being driven by users so much as it is by the developers. And Twitter is a prime example. Seeking Consistency Across All Platforms Twitter is discontinuing Twitter...

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How to Control Your Arduino Using JavaScript


control-arduino-js

Arduino boards are one of the easiest ways to get into hardware hacking for programmers. There are a huge array of beginner projects out there to suit almost anyone with a programming background. Even so, getting started can seem daunting for those short on time. Learning a totally new language just to try out a microcontroller might seem like a lot of work. What if you want to start playing around with home-brew electronics in a program language you are already familiar with? Good news: you can! We’ve already showed you how to control an Arduino board with Python, and...

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5 Reasons Why You Shouldn’t Host Your Own Videos


shouldnt-host-own-videos

Whether you’re looking for an alternative to YouTube or simply want to retain control over your videos, self-hosting videos is an attractive option. But does it really solve anything? You might have been hit by YouTube’s changes to monetization. Even then, it could work out better on your pocket to avoid hosting your own videos. Plenty of alternatives are available (such as Vimeo), and one of them will almost certainly meet your needs better than self-hosting. Here’s why you shouldn’t host your own videos. The Difference Between Self-Hosted and Embedded Before we look into the reasons not to self-host your...

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Norton WiFi Privacy Helps Protect Your Browsing Anywhere You Go


norton-wifi-privacy

By now, you hopefully know that it’s vital to use a virtual private network (VPN) when you’re online. They keep your transactions secure and help you enjoy online privacy! Free VPNs may not cut it. If you’re looking for a solid solution, check out Norton WiFi Privacy. What Is Norton WiFi Privacy? Norton WiFi Privacy is a paid VPN service that helps keep you secure online. Without it, many entities could track your browsing and analyze your habits. Public Wi-Fi networks, like those in coffee shops, could leave you vulnerable without a VPN. Norton WiFi Privacy can keep your browsing safe when...

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Perform Text Analysis with IBM Watson and Google Docs


Google, Microsoft, IBM and Amazon have made it easier for developers to add human cognitive capabilities (also known as artificial intelligence) within their own applications. You need not be a machine learning expert to build a computer program that can recognize objects in photographs, or one that transforms human speech to text or even a chatbot that converses with people in natural language.

The Google Photos app leverages machine learning to identify landmarks and faces in your photos. You can even build and train your own machine learning models by installing Google’s TensorFlow library on your own computer. IBM’s PowerAI lets enterprises deploy TensorFlow like frameworks in the cloud on power systems for training custom machine learning models of any size.

The IBM Code Patterns microsite hosts hundreds of ready-to-use examples around artificial intelligence. For instance, here’s an open source repo that explains how to recognize images of houses that have swimming pools. Another example on Github shows how you can easily build a system that can detect and count products on store shelves using the PowerAI platform.

Train your own Machine Learning Model

If you would like to build your own image recognition engine without the complexity of servers and TensorFlow, try this online demo of the Watson Visual Recognition engine hosted the IBM Cloud (formerly Bluemix) website.

watson-image-recognition.png

You can create your own classifier and upload a set of images to train the classifier.  It is also essential to upload a set of negative images that may look similar but are different. Train the model and, in about a minute or so, your model is ready. Upload any image and the classifier will be able to tell if it matches any of your trained bundles.

IBM Watson + Google Docs for Natural Language Understanding

The Natural Language Processing (NLP) service of IBM Watson uses machine learning to extract entities, person names, places, and understand the overall sentiment and emotion of text. Amazon Comprehend and Google Natural Language are other competing platforms that offer powerful text analysis in the cloud.

ibm-watson-nlp.png

Getting started with Watson NLP is easy and all you need is an IBM Cloud account to get started. The lite plan is free (no credit card required), it never expires and the quota resets every month automatically.

I’ve built a sample Google Apps Script based app that uses Watson NLP to analyze the text in your Google Document. Here’s how you can get started:

  1. Copy this Google Document to your Google Drive
  2. Select the text in the document, go to the IBM Watson menu and choose the Analyze text menu.
  3. Grant the necessary authorization and you’ll see get a pop-up with the list of entities found in the selected text.

The Google Apps Script is open-source and you can find a copy of the source code inside Tools > Script Editor. If you ever run into quota limits, remember to replace the credentials in the source code with your own Bluemix account.

ibm-watson-google-docs.gif

Disclaimer: The writer attended IBM Code Day in Bangalore at the invitation of IBM. The travel and accommodation were arranged and paid for by IBM.


The Best Browser Extensions for Listening to Podcasts


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Podcasts can entertain you, educate, and give you updates on topics that matter. Many people listen to them on their smartphones and tablets, or in the car through streaming services. But in some situations, it may be more convenient to listen to a podcast through your web browser. Fortunately, there are numerous browser extensions to help you listen to podcasts without fuss. And we have seven of the best for you below. 1. SmarterPod Currently available in beta, this browser extension lets you sign up to podcast feeds. That means you need never miss episodes of your favorite storytelling podcasts...

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Use Excel’s Forecast Function to Turn Historical Data Into Predictions


forecast-excel

Microsoft can’t predict the future — but it can sure try. Excel’s time series forecasting abilities take data you’ve provided and extrapolate potential future data. It’s not perfect, but it can give you an idea of what your data is really telling you. A tiny glimpse into the future, if you will. There are two different ways to forecast in Excel. First, you can use several forecast functions directly within the cells of your spreadsheet. The second method, which uses a graphical interface, is easier to use, so we’ll be focusing on that. If you really want to know how...

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Facebook’s tracking of non-users ruled illegal again


 Another blow for Facebook in Europe: Judges in Belgium have once again ruled the company broke privacy laws by deploying technology such as cookies and social plug-ins to track Internet users across the web. Read More
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Obliviate Sends Secret, Self-Destructing Messages to Anyone


Obliviate is a new app from MakeUseOf that lets you send self-destructing messages. It’s great for sharing secret messages with friends that you don’t want sticking around on their phone, among other use cases. Download: obliviate for Android and iOS. The app lets you set a timer between 5 and 180 seconds for how long your messages will last. Once the recipient opens it, the message will disappear after a set time. And if you change your mind, you can immediately obliviate messages and bypass the timer. Best of all, the obliviate is free and has no ads; never will....

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How to Translate Phrases Using Alexa and Google Home


With the many things that the Amazon Echo and Google Home can do, it’s no surprise that translating phrases is on that list. But how do the two devices compare when it comes to translating from English into other languages? How to Translate Phrases Using Alexa To translate words or phrases with the Amazon Echo you can use basic phrases like: “Alexa, how do you say [phrase] in [language]?” Some of the languages that worked for us included Spanish, German, French, Japanese, Swedish, Korean, and Italian, and the translations are powered by Bing. If you want access to a longer...

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Google’s Tez payments app now lets users handle their utility bills and more


 Google’s Tez payment service in India has got a major update that allows users to pay their utilities and other bills via the app. The service was launched last September for iOS and Android and it initially allowed for payments between bank accounts using India’s UPI (Unified Payments Interface) protocol. Now the app has gotten support to pay for bills from more than 80… Read More
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This Awesome Game by Google Teaches Your Kids to Stay Safe Online


Today, kids face cyber threats every second they are online. Unfortunately, kids will only learn so much about internet safety from articles and videos. If you really want those lessons to stick, a game might have a longer lasting impact. Perhaps that’s why Google created an internet safety game of their own. Show them the link because you shouldn’t leave the safety of your children to chance. Google calls it “Be Internet Awesome” but the Interland game is the fun part of it as it takes kids on an adventure where they get to battle cyberbullies, hackers, phishers, and even outsmart...

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How to Sideload an App on Roku


best-free-roku-channels

You can use one of four different methods to add channels to your Roku device. The three most common are the web version of the official channel store, the on-device version of the channel store, and adding private channels by using a unique code. The fourth method—sideloading—is less widely used. Sideloading is the most complicated method, but it’s also the only approach that’ll let you add absolutely any channel you want, even if it’s not in the channel store and it doesn’t have a unique code. And if you have the source code of an app, it’s also a great...

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Technological solutions to technology’s problems feature in “How to Fix The Future”


 In this edition of Innovate 2018, Andrew Keen finds himself in the hot seat. Keen, whose new book, “How to Fix the Future”, was published earlier this month, discusses a moment when it has suddenly become fashionable for tech luminaries to abandon utopianism in favor of its opposite.  The first generation of IPO winners have now become some of tech’s most vocal… Read More
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Fake news is an existential crisis for social media 


 Every gun outrage in America is now routinely followed by a flood of Russian-linked Twitter bot activity. Exacerbating social division is the name of this game. And it’s playing out all over social media continually, not just around elections. Read More
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Fake news is an existential crisis for social media 


 Every gun outrage in America is now routinely followed by a flood of Russian-linked Twitter bot activity. Exacerbating social division is the name of this game. And it’s playing out all over social media continually, not just around elections. Read More
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