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DNN Detection and Clinical Staging of COVID-19 Chest X-rays

Wolfram and other DNNs were adapted for COVID-19 detection on chest x-rays with up to 100% accuracy on 1,200 training images. Another DNN had 80% accuracy for COVID-19 staging on 80 images. Methods to improve training data with routine and AI-assisted quality assurance are discussed and assessed.

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Conrad Wolfram
Robert Knapp
Anthony Zupnik
Sabine Fischer
Ana Moura Santos
Jon McLoone
Julius Hannink
Albert Retey
Dragan Simic
Dominik Dvorak
Jan Brugård
Bernat Espigule-Pons
Giulio Alessandrini
Mária Bohdalová
Matthew Fairtlough
Jan Poeschko
Tom Wickham-Jones
Jan Brugård
Robert Knapp
This talk will be an introduction to and summary of many of the numerical computation capabilities built into Mathematica, including arbitrary precision arithmetic, numerical linear algebra, optimization, integration, and differential ...
Tatjana Samardzic
This paper describes a Mathematica and SystemModeler platform for automated, fast analog filter design and simulation. The platform consists of two key components: