*Students and faculty team of Rajalakshmi Group behind this breakthrough innovation.

But still, COVID-19 continues to spread rapidly across the world snatching away the lives of many.Hence, in a bid to help the Central and the State Governments and also the people, a team of students and faculty from Rajalakshmi Group of Institutions, has developed a breakthrough software to detect COVID-19.The AI (Artificial Intelligence) tool is based on neural network to detect COVID-19, CAP (Community-Acquired Pneumonia) and normal condition from chest X-Ray images.

A whopping number of 14148 images were used in the training process and the tool has testing accuracy of 95.4 percent.The highlights of the tool are:* No installation required.

It is a simple website which can be accessed from anywhere.

S. Rajkumar, Professor & Head,  Department of Biomedical Engineering; Dr. V. Sapthagirivasan, Professor,BME; Mr.V.Rajaraman, Assistant Professor, CSE;Mr. Ashwin Ramesh III Year CSE ( student )are the members of the team that developed the unique software.

All the above are part of Centre of Medical Imaging of Rajalakshmi Group of Institutions.Dr Haree S Meganathan from the management of Rajalakshmi Institutions said, “It is a matter of immense pride that our students and staff have developed this AI based platform to detect COVID-19 cases.

Rajalakshmi group of educational institutions in Chennai is familiar for their versatility of academic excellence and research activities.

In the group, Centre for Medical Imaging is formed with the objective of creating proficient solutions in medical imaging applications.

The centre has members from faculty fraternity, students, and medical imaging professionals.Ever since the onset of the pandemic COVID-19, the members of the centre discusses the research progress across global in the aspect of medical imaging to detect COVID-19 through various imaging modalities like X-Ray.

Initially, we were thinking to use ultrasound images but due to some technical issues, we couldn’t follow it up.Later we decided to use chest X-ray images and incidentally, we were able to get around 100 COVID-19 affected subjects’ chest X-ray images through open-source Canadian research forum.

With the acquired images we planned to develop an Artificial Intelligence (AI) tool to detect COVID-19 condition from the test chest X-ray image.We decided to add the provision for detecting CAP (Community-Acquired Pneumonia) besides to COVID-19 in the proposed tool.

We used 14,148 chest X-ray images of all these three classes for rigorously training the neural network inbuilt in the AI tool.

Are you confident in Python Programming?

Also, be ready to learn the ‘Go’ Programming Language which is chasing Python to win the race!‘Go’ also called Golang is a general-purpose language developed by Google a decade ago.

Though AI application developers and Data scientists are crazy with the features of Python, there are certain issues and challenges in Python that can slow up the process of developing AI applications in the near future.Few major issues are:Slow executionLack of support to concurrency The dynamic allocation of data types further reduces the speed in Python The Go Programming language overcomes these issues.

Go is a procedural and open source programming language developed by Robert Griesemer, Rob Pike, Ken Thompson at Google in 2007.

It is statically typed and compiled, fast executing language like C++ and Java.

Go provides a wide range of powerful tools that helps to develop highly efficient products.

Capabilities are available over the network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, tablets, laptops, and workstations).• Resource pooling.

The provider’s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to consumer demand.

Examples of resources include storage, processing, memory, and network bandwidth.• Rapid elasticity.

To the consumer, the capabilities available for provisioning often appear to be unlimited and can be appropriated in any quantity at any time.• Measured service.

The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings.Examples: SaaS: Google Apps, Dropbox, Salesforce, Cisco WebEx, Concur, GoToMeeting• Platform as a Service (PaaS): The capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages, libraries, services, and tools supported by the provider.

The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, or storage, but has control over the deployed applications and possibly configuration settings for the application-hosting environment.Examples: PaaS: AWS Elastic Beanstalk, Windows Azure, Heroku, Force.com, Google App Engine, Apache Stratos, OpenShift• Infrastructure as a Service (IaaS): The capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications.