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COVID-19 diagnosis using AI

TopicLeading institutions, researchers & key papers

COVID-19 diagnosis using AI is a topic indexed in ScholarIQ from OpenAlex.

What is known about COVID-19 diagnosis using AI?

ScholarIQrecord summary

This cluster of papers focuses on the application of deep learning, particularly convolutional neural networks, in medical imaging for the detection and diagnosis of COVID-19, pneumonia, and other thoracic diseases using chest X-ray and CT scan images. The research explores the use of artificial intelligence, transfer learning, and image-based deep learning techniques to develop automated systems for accurate medical diagnoses.

How many works does COVID-19 diagnosis using AI have?

ScholarIQindexed works

COVID-19 diagnosis using AI has 54,817 works in the ScholarIQ index. The count is the OpenAlex total, not the number of papers listed on this page.

How many citations does COVID-19 diagnosis using AI have?

ScholarIQcitation count

COVID-19 diagnosis using AI has 608,516 citations in the OpenAlex counts ScholarIQ stores.

What is the OpenAlex record for COVID-19 diagnosis using AI?

ScholarIQopenalex

The OpenAlex for COVID-19 diagnosis using AI is on the source record.

Who are the most-cited researchers behind COVID-19 diagnosis using AI?

ScholarIQtop researchers by citations
1
Geoffrey E. Hinton · Neural Networks and Applications
385 works451,920 citations
2
Walter C. Willett · Nutritional Studies and Diet
2,701 works408,557 citations
3
Peer Bork · Genomics and Phylogenetic Studies
950 works390,812 citations
4
Ross Girshick · Advanced Neural Network Applications
175 works355,032 citations
5
John P. A. Ioannidis · Meta-analysis and systematic reviews
1,851 works312,766 citations

Where is COVID-19 diagnosis using AI research published, and who funds it?

ScholarIQvenues & funding sources

TOP JOURNALS

No journal data available yet.

TOP FUNDERS

National Science Foundation—
NIH—
Wellcome Trust—
European Research Council—
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