AI and Point of Care Image Analysis for COVID-19

Michael Roberts; Oz Frank; Shai Bagon; Yonina C. Eldar; Carola Bibiane Schönlieb

doi:10.1007/978-3-031-08506-2_4

AI and Point of Care Image Analysis for COVID-19

Michael Roberts, Oz Frank, Shai Bagon, Yonina C. Eldar, Carola Bibiane Schönlieb

Department of Computer Science and Applied Mathematics

Weizmann Institute of Science

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Point-of-care imaging, including chest X-ray, computed tomography and ultrasound have played a critical role in the response to COVID-19. Clinicians study the patterns and changes in the images to make a likely diagnosis, assess a patients clinical response and to predict likely outcomes. In this chapter we focus on the application of artificial intelligence (AI) techniques to these imaging modalities and discuss the contributions in the literature for diagnosis and prognostic models.

Original language	English
Title of host publication	Artificial Intelligence in Covid-19
Chapter	4
Pages	85-119
Number of pages	35
ISBN (Electronic)	9783031085062
DOIs	https://doi.org/10.1007/978-3-031-08506-2_4
State	Published - 10 Nov 2022

All Science Journal Classification (ASJC) codes

General Computer Science
General Medicine

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10.1007/978-3-031-08506-2_4

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AI and Point of Care Image Analysis for COVID-19

Abstract

All Science Journal Classification (ASJC) codes

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