United in Purpose: Software Innovators Contribute to the COVID-19 Response

Published: 05/13/2020

Nicole Huesman, community and developer advocate, Intel Corporation
@IntelDevTools


The coronavirus (COVID-19) global pandemic has united our communities, even as we adhere to shelter-in-place stipulations. Never have science and technology been more important in helping us navigate these extraordinarily challenging times to emerge stronger.

Here, we highlight three software innovators from Intel who are pursuing worthwhile medical research projects to contribute to this critical effort.

 

Seeking Early Detection Using Medical Image Processing

 

With quick escalation and spread of the COVID-19 virus, early recognition is vital not only for prompt treatment, but also for patient isolation and effective public health containment and response. Moloti Tebogo Nakampe, a stochastic algorithm engineer from the University of Cape Town in South Africa, has proposed the use of artificial intelligence-based computer tomography (CT) image analysis for the recognition of COVID-19 infection. Moloti proposes the use of technologies such as Intel® oneAPI AI Analytics Toolkit, machine-learning and deep-learning frameworks optimized by Intel, Intel® oneAPI Math Kernel Library, Intel® Distribution for Python*, and Intel® DevCloud.

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Identifying Effective Treatment by Applying Computational Methods

 

Given the lack of effective drugs and vaccines to treat COVID-19, Ho Leung Ng, associate professor of biochemistry and biophysics from Kansas State University, aims to develop and apply computational methods to rapidly identify potential drug candidates for treatment of the disease, aided by technologies including the Intel oneAPI Math Kernel Library and Intel Distribution for Python. To accelerate drug discovery in the face of this global emergency, Ng’s approach focuses on the following two aspects:

  • Investigate clinically used, well-studied experimental drugs that have a higher chance of efficacy without toxicity or side effects.
  • Employ new machine-learning strategies to generate and evaluate drug candidate molecules.

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Slowing the Spread through Computer Vision and Deep-Learning Techniques

 

Alessandro de Oliveira Faria, a software developer at Oiti Technologies in Brazil, is currently working on a project that employs artificial intelligence to minimize contagion of COVID-19. The project uses algorithmic data, which is supported by Intel® Distribution of OpenVINO™ toolkit, to obtain an estimate of the number of people and vehicles traveling within a specific region, and calculates the necessary distance between individuals to reduce spread of the virus.

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We are proud to support them in their endeavors and hope all of our colleagues and communities around the world stay healthy and safe.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.