Artificial intelligence–enabled rapid diagnosis of patients with COVID-19 (Registro nro. 5980)
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fixed length control field | 02563nam a22003017c 4500 |
001 - CONTROL NUMBER | |
control field | 00005980 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | ES-MaONT |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20211006062659.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 200525t2020 |||||o|||| 00| 0 eng d |
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER | |
International Standard Serial Number | 1078-8956 |
040 ## - CATALOGING SOURCE | |
Original cataloging agency | ES-MaONT |
100 ## - MAIN ENTRY--PERSONAL NAME | |
Personal name | Mei, Xueyan |
9 (RLIN) | 4475 |
245 00 - TITLE STATEMENT | |
Title | Artificial intelligence–enabled rapid diagnosis of patients with COVID-19 |
260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
Name of publisher, distributor, etc. | Nature Medicine, |
Date of publication, distribution, etc. | 2020 |
300 ## - PHYSICAL DESCRIPTION | |
Extent | 14 págs. |
336 ## - CONTENT TYPE | |
Source | isbdcontent |
Content type term | texto (visual) |
337 ## - MEDIA TYPE | |
Source | isbdmedia |
Media type term | electrónico |
338 ## - CARRIER TYPE | |
Source | rdacarrier |
Carrier type term | recurso en línea |
520 ## - SUMMARY, ETC. | |
Summary, etc. | For diagnosis of coronavirus disease 2019 (COVID-19), a SARS-CoV-2 virus-specific reverse transcriptase polymerase chain reaction (RT–PCR) test is routinely used. However, this test can take up to 2 d to complete, serial testing may be required to rule out the possibility of false negative results and there is currently a shortage of RT–PCR test kits, underscoring the urgent need for alternative methods for rapid and accurate diagnosis of patients with COVID-19. Chest computed tomography (CT) is a valuable component in the evaluation of patients with suspected SARS-CoV-2 infection. Nevertheless, CT alone may have limited negative predictive value for ruling out SARS-CoV-2 infection, as some patients may have normal radiological findings at early stages of the disease. In this study, we used artificial intelligence (AI) algorithms to integrate chest CT findings with clinical symptoms, exposure history and laboratory testing to rapidly diagnose patients who are positive for COVID-19. Among a total of 905 patients tested by real-time RT–PCR assay and next-generation sequencing RT–PCR, 419 (46.3%) tested positive for SARS-CoV-2. In a test set of 279 patients, the AI system achieved an area under the curve of 0.92 and had equal sensitivity as compared to a senior thoracic radiologist. The AI system also improved the detection of patients who were positive for COVID-19 via RT–PCR who presented with normal CT scans, correctly identifying 17 of 25 (68%) patients, whereas radiologists classified all of these patients as COVID-19 negative. When CT scans and associated clinical history are available, the proposed AI system can help to rapidly diagnose COVID-19 patients. |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | Sanidad digital |
Source of heading or term | |
9 (RLIN) | 2065 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
9 (RLIN) | 4348 |
Topical term or geographic name entry element | Inteligencia Artificial |
653 ## - INDEX TERM--UNCONTROLLED | |
Uncontrolled term | coronavirus |
653 ## - INDEX TERM--UNCONTROLLED | |
Uncontrolled term | COVID-19 |
653 ## - INDEX TERM--UNCONTROLLED | |
Uncontrolled term | deep learning |
856 4# - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://www.nature.com/articles/s41591-020-0931-3 |
Nonpublic note | Abierto |
Link text | Acceso al artículo |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Source of classification or shelving scheme | |
Koha item type | Artículos |
Withdrawn status | Lost status | Materials specified (bound volume or other part) | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type | Public note |
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Artículo | Acceso libre online | Colección digital | CDO | CDO | 25/05/2020 | 1000020176183 | 25/05/2020 | 25/05/2020 | Artículos | .pdf, .html |