Software Engineering Insights

The radiology wing of hospital systems and diagnostic centers generates an abundance of sensitive data. However, they often lack the analytics infrastructure to access and parse the data efficiently. To make the most of this available big data, radiologists are leveraging AI-based imaging analytics.

It was the 1950s' when Alan Turing conceptualized Artificial Intelligence. Nobody would have imagined the vast array of applications that this technology could offer. He formed the mathematical & logical reasoning behind the concept of machines and computers replicating human intelligence, which today has outgrown to even replace humans for certain tasks. 

We are all aware of chatbots and how they interact with us. And we all have invariably wished if only they were more human-like. 

Admit it, it is pesky to be interacting with a bot especially when it fails to understand your core issues. That’s when you wish if only you were talking to a human than a virtual assistant.

It was 31st December when WHO’s Country Office in the People’s Republic of China got the news from a media statement by Wuhan Municipal Health Commission, of a case of “viral pneumonia” in Wuhan, capital of Central China’s Hubei province. What seemed to be a “viral pneumonia”, after detailed studies were coined as a novel coronavirus, thus marking the inception of the COVID-19 pandemic.  

Converting prospects into customers­ – the ultimate goal of closing more sales – depends on how you prospect your customers.

Are you doing it any differently? By differently we mean using automation to nudge your prospect to take the next step in the journey. If yes, it’s great if not then read on.

Humans have exceptional power for image recognition. High-level image understanding, contextual knowledge, and the ability for parallel processing are some of the factors that contribute to precise recognition of objects, places, people, writing, and actions. However, humans develop these abilities over time and have a limitation as well. When it comes to recognizing images from a large set of data, human processing power might fail.

Machine Learning is one of the proficient technologies that we have for pattern recognition, data mining, statistical analysis on large volumes of data. It’s enabling machines to recognize intricate patterns and make intelligent decisions, without human intervention. In order to achieve this, the ML technology is accompanied by neural networks.

The human brain has got tremendous potential. On an everyday basis, it performs hundreds and thousands of tasks- such as recognizing faces, learning from experiences, memorizing facts, identifying objects, understanding words & languages, recognize intent & sentiments, and more. There are billions of neurons in the brain that network together to accomplish these tasks.

The COVID-19 pandemic has affected over 9 million lives worldwide. The virus infection is disseminating like wildfire, putting pressure on the global economy and marking a downfall of various businesses. 

For humans, classifying objects in an image is straightforward, as compared to machines. This process of classifying objects in an image, known as Image Classification involves labeling of images into predefined classes. Since there can be  n number of classes into which an image can be classified, manual classification (when there are thousands of images) is difficult for humans too. That is why automating the process of object identification and classification with machines is gaining ground.