Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloArtificial Intelligence Applied to Chest X-ray for Differential Diagnosis of COVID-19 Pneumonia
Anno di pubblicazione2021
FormatoElettronico
Autore/iSalvatore C.; Interlenghi M.; Monti C.B.; Ippolito D.; Capra D.; Cozzi A.; Schiaffino S.; Polidori A.; Gandola D.; Alì M.; Castiglioni I.; Messa C.; Sardanelli F.
Affiliazioni autoriDepartment of Science, Technology, and Society, Scuola Universitaria IUSS, Istituto Universitario di Studi Superiori, Piazza della Vittoria 15, 27100 Pavia, Italy. DeepTrace Technologies S.R.L., via Conservatorio 17, 20122 Milano, Italy. Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy. Department of Radiology, ASST Monza-Ospedale San Gerardo, Via Pergolesi 33, 20900 Monza, Italy. Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy. Department of Diagnostic Imaging and Stereotactic Radiosurgery, C.D.I. Centro Diagnostico Italiano S.p.A., Via Saint Bon 20, 20147 Milano, Italy. Department of Physics, Università degli Studi di Milano-Bicocca, Piazza della Scienza 3, 20126 Milano, Italy. Institute of Biomedical Imaging and Physiology, Consiglio Nazionale delle Ricerche, Via Fratelli Cervi 93, 20090 Segrate, Italy. School of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Piazza dell'Ateneo Nuovo 1, 20126 Milano, Italy. Fondazione Tecnomed, Università degli Studi di Milano-Bicocca, Palazzina Ciclotrone-Via Pergolesi 33, 20900 Monza, Italy.
Autori CNR e affiliazioni
  • ISABELLA CASTIGLIONI
Lingua/e
  • inglese
AbstractWe assessed the role of artificial intelligence applied to chest X-rays (CXRs) in supporting the diagnosis of COVID-19. We trained and cross-validated a model with an ensemble of 10 convolutional neural networks with CXRs of 98 COVID-19 patients, 88 community-acquired pneumonia (CAP) patients, and 98 subjects without either COVID-19 or CAP, collected in two Italian hospitals. The system was tested on two independent cohorts, namely, 148 patients (COVID-19, CAP, or negative) collected by one of the two hospitals (independent testing I) and 820 COVID-19 patients collected by a multicenter study (independent testing II). On the training and cross-validation dataset, sensitivity, specificity, and area under the curve (AUC) were 0.91, 0.87, and 0.93 for COVID-19 versus negative subjects, 0.85, 0.82, and 0.94 for COVID-19 versus CAP. On the independent testing I, sensitivity, specificity, and AUC were 0.98, 0.88, and 0.98 for COVID-19 versus negative subjects, 0.97, 0.96, and 0.98 for COVID-19 versus CAP. On the independent testing II, the system correctly diagnosed 652 COVID-19 patients versus negative subjects (0.80 sensitivity) and correctly differentiated 674 COVID-19 versus CAP patients (0.82 sensitivity). This system appears promising for the diagnosis and differential diagnosis of COVID-19, showing its potential as a second opinion tool in conditions of the variable prevalence of different types of infectious pneumonia.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da530
Pagine a-
Pagine totali12
RivistaDiagnostics (Basel)
Attiva dal 2009
Editore: Molecular Diversity Preservation International - Basel
Lingua: inglese
ISSN: 2075-4418
Titolo chiave: Diagnostics (Basel)
Titolo proprio: Diagnostics. (Basel)
Titolo abbreviato: Diagnostics (Basel)
Numero volume della rivista11
Fascicolo della rivista3
DOI10.3390/diagnostics11030530
Verificato da referee-
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)-
Parole chiaveCOVID-19; SARS-CoV-2; artificial intelligence; chest X-ray; community-acquired pneumonia; differential diagnosis; neural networks; sensitivity; specificity.
Link (URL, URI)https://www.mdpi.com/2075-4418/11/3/530
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione11/03/2021
Note/Altre informazioni-
Strutture CNR
  • IBFM — Istituto di bioimmagini e fisiologia molecolare
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-
Allegati