publication . Other literature type . Preprint . 2020

Unveiling COVID-19 from Chest X-ray with deeplearning: a hurdles race with small data

Tartaglione, Enzo; Barbano, Carlo Alberto; Berzovini, Claudio; Calandri, Marco; Grangetto, Marco;
Open Access English
  • Published: 10 Jun 2020
  • Publisher: Zenodo
Abstract
The possibility to use widespread and simple chestX-ray (CXR) imaging for early screening of COVID-19 patientsis attracting much interest from both the clinical and the AIcommunity. In this study we provide insights and also raisewarnings on what is reasonable to expect by applying deeplearning to COVID classification of CXR images. We providea methodological guide and critical reading of an extensive set ofstatistical results that can be obtained using currently availabledatasets. In particular, we take the challenge posed by currentsmall size COVID data and show how significant can be thebias introduced by transfer-learning using larger public non-COVID CXR da...
Subjects
free text keywords: Chest X-ray, Deep Learning, Classification, COVID-19
Funded by
EC| DeepHealth
Project
DeepHealth
Deep-Learning and HPC to Boost Biomedical Applications for Health
  • Funder: European Commission (EC)
  • Project Code: 825111
  • Funding stream: H2020 | IA
Communities
COVID-19
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Zenodo
Other literature type . 2020
Provider: Datacite
Zenodo
Other literature type . 2020
Provider: Datacite
ZENODO
Preprint . 2020
Provider: ZENODO
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publication . Other literature type . Preprint . 2020

Unveiling COVID-19 from Chest X-ray with deeplearning: a hurdles race with small data

Tartaglione, Enzo; Barbano, Carlo Alberto; Berzovini, Claudio; Calandri, Marco; Grangetto, Marco;