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AI-Research Evolution. A Snapshot in Pandemic | by Harsha Angeri | Aug, 2020

A Snapshot in Pandemic

Harsha Angeri

Artificial Intelligence (AI) has seen exponential growth. Research paper filings in AI have followed suit and more than 30,000 have been filed on arxiv.org.

Pandemic has affected AI research too and can be seen in the drop of submissions in recent months

However healthcare-focused research has seen an upsurge with a spike during the pandemic.

AI research has become very multidisciplinary over the years as can be seen below. In addition to core disciplines of AI & Machine Learning, Computer Vision research has dominated over the years including Image & Video processing. Disciplines of Neural Computing, Robotics, Signal Processing & Language have also seen a good chunk of research.

During the pandemic, some of these areas continue to dominate. Here are a top few filing disciplines.

However, certain biological/ medical disciplines have seen an upsurge in AI-led research during the pandemic. Research around Biomolecules, Tissues & Organs, Molecular Networks, Medical/ Biological Physics, and Genomics has picked up.

CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), GANs (Generative Adversarial Networks) & other algorithms using GPUs dominate across the years.

Top Few Concepts Across The Years

During the pandemic, the upshot in medical research has seen a lot of focus on X-Rays, CT scans, EEG, 3D image analysis & RNA focused methods. QA systems to query journals for faster access to answers or patterns have also seen an upsurge. Explainable AI (XAI) has taken precedence, especially in medical diagnosis.

Diseases that AI is applied to has also shifted over the years. Cancer research is the main focus. In recent months Pneumonia related research has seen an increase. Diabetes continues to be a major focus area across the years.