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Visual aesthetics has been shown to critically affect a variety of constructs such as perceived usability, satisfaction, and pleasure. However, visual aesthetics is also a subjective concept and therefore, presents its unique challenges in training a machine learning algorithm to learn such subjectiveness.

Given the importance of visual aesthetics in human-computer interaction, it is vital that machines adequately assess the concept of visual aesthetics. Machine learning, especially deep learning techniques have already shown great promise on tasks with well-defined goals such as identifying objects in images or translating from one language to another. However, quantification of image aesthetics has been one of the most persistent problems in image processing and computer vision.
We decided to build a deep learning system that can automatically analyze and score an image for aesthetic quality with high accuracy. …


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Sentiment analysis is contexual mining of text which identifies and extracts subjective information in source material, and helping a business to understand the social sentiment of there brand, product or service while monitoring online conversations. However, analysis of social media streams is usually restricted to just basic sentiment analysis and count based metrics. This is akin to just scratching the surface and missing out on those high value insights that are waiting to be discovered. So what should a brand do to capture that low hanging fruit?

With the recent advances in deep learning, the ability of algorithms to analyse text has improved considerably. Creative use of advanced artificial intelligence techniques can be an effective tool for doing in-depth research. We believe it is important to classify incoming customer conversation about a brand based on following…


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In our previous blog post of Visual Analytics we discussed Instagram’s #gopro hashtag using AI. In this blog post, we will be exploring #Kendrick Lamar on Instagram. Kendrick Lamar’s DAMN released this April with tons of rave reviews. Christopher R. Weingarten of Rolling Stone writer describing it as a combination of “the old school and the next-level.” It marked his third #1 album on the Billboard 200 chart, and the single “Humble” became his first #1 as a lead artist on the Billboard Hot 100. …


Research has established that a large percentage of dental caries escape identification in routine dental examinations, even when such examinations include dental x-rays. Certain types of caries, like occlusal caries, appear to be easier to find through a normal clinical examination or x-ray review, whereas diagnosing other types of caries, such as caries below the surface of the tooth, interproximal caries, and root caries, is often not as reliable.

At ParallelDots, Inc. we took the challenge to find these dental anomalies with human-level accuracy and build a reliable diagnostic tool for the dentists. In this blog post, we will discuss the recent study we did for our automated caries detection system, putting our system against three practicing dentists from North American clinics. We found that our system had a higher agreement (F Score) with clinically verified ground truth than all three individually (the difference between system’s F Score and average F-Score of the dentists is over 17%). Our system has higher sensitivity with respect to Dentists individually and hence can be used as a tool to ease the work of dentists by suggesting them possible caries they can then verify and treat. A breakdown of metrics in our test is given in the table below. …


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Last week, we launched ParallelDots Excel add-in, a solution for using ParallelDots NLP APIs to do text analysis on unstructured data without writing a single line of code. The Excel add-in is very easy to use and provides a convenient, yet effective solution for your text analysis needs. In an earlier post, we provided you with detailed information of how the excel add-in works. In this post, we will discuss some real-world use cases where you can use the Excel Add-in to raise your analytics game without spending a fortune on building a data science team.

Text analysis on product reviews from E-commerce sites, Facebook Pages and other review sites

You can analyze a corpus of customer reviews to understand the general impression about your product. The Excel add-in works on ParallelDots AI APIs, which are being used extensively by developers and enterprises to empower their analytics since the last two years. …


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Images have become a very common medium of human expression on the internet with the coming up of social networks. Facebook is the biggest repository of digital images ever. This trend is only going to intensify given the emergence of image first platforms like Instagram and Snapchat, also called “Visual Social Media”. Marketers and analysts generally find it really hard to gather insights from these visual social media, because its hard to quantify images being shared. The answer lies in automated image analytics i.e. Visual Analytics that can process the visual information and derive conclusions. Until very recently, it wasn’t even possible to do such automated analytics but times have changed. Now Visual Analytics tools are used to get the analysis of images.
With the recent success of deep learning models called convolutional neural networks in automated perception tasks, AI has matured enough to act as a proxy to human observers to document what is being shared. These AI algorithms can actually make sense of what the content of the image is (for instance, it can see that the image contains dogs or cats or an apple) and even asses various quantities for us (Microsoft recently released a demo where they could estimate the age of the person in the image). …


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Our Excel Add-in provides state-of-the-art text analysis capabilities without writing a single line of code. The add-in also comes in handy when you need to run text analysis in batches on a large corpus of text and discover insights in them (such as user-generated content from social media campaigns, earnings call transcripts, open-ended user feedback etc.). You can export all your data from any BI tool you use in xlsx (or CSV format) and install our plugin to annotate the data with sentiment, emotions, intent etc. and analyze them from the comfort of your spreadsheet.

In this post, we will show you how to use our Excel Add-in to add an important tool to your text analytics and text mining capabilities. …


Note: This is the second post of the series Data Tagging in Medical Imaging. You can find the first post here.

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In the previous post of the series, Data Tagging in Medical Imaging, we gave you an overview of the kind of processes that you must put in practice to scale your data tagging engine. In this blog we will thoroughly discuss how to come up with these processes and things to consider before finalizing and formulating these processes. We will be discussing what these processes are and how they affect the data tagging process.

First of all, you need some resources to set up these processes. To set up them up, you need to make sure the availability of the…


Today, as we are witnessing the era of smart AI-driven solutions which are empowering humans to automate tasks that require a certain level of cognition. One major reason for this shift in developing AI-driven products is the availability of a large amount of data. As we, humans, tend to learn through various experiences throughout our life, machines learn and automate tasks based on the data fed to them.

From our experience in developing vertical agnostic AI-first products, we are well aware of the importance of the availability of quality data and subsequently developing a smart data tagging process. In this series of blog posts, we’re going to talk about the importance of data tagging in medical imaging, where we are developing computer vision technologies to better assist doctors. …


“Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before — as long as we manage to keep the technology beneficial.“
-Max Tegmark, President of the Future of Life Institute

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Picture credits: iReviews

Artificial Intelligence has made its way to every field possible, steamrolling the processes along its way. One such field is healthcare. They say healthcare is a field that is not very rules based and a successful doctor is the one who leverages his/her experience to deal with complex and unseen cases. However, there are many low hanging fruits that are already being plucked by AI. This trend is being fueled by increasing digitization in healthcare data and advances in new algorithms. In this piece, we intend to give you a sneak peek into how AI is leading to improved healthcare for humanity. …

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