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The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs.
Lakhani, Paras; Mongan, J; Singhal, C; Zhou, Q; Andriole, K P; Auffermann, W F; Prasanna, P M; Pham, T X; Peterson, Michael; Bergquist, P J; Cook, T S; Ferraciolli, S F; Corradi, G C A; Takahashi, M S; Workman, C S; Parekh, M; Kamel, S I; Galant, J; Mas-Sanchez, A; Benítez, E C; Sánchez-Valverde, M; Jaques, L; Panadero, M; Vidal, M; Culiañez-Casas, M; Angulo-Gonzalez, D; Langer, S G; de la Iglesia-Vayá, María; Shih, G.
  • Lakhani P; Department of Radiology, Thomas Jefferson University, Sidney Kimmel Jefferson Medical College, 111 S 11th St, Philadelphia, PA, 19107, USA. paras.lakhani@jefferson.edu.
  • Mongan J; University of California San Francisco, San Francisco, CA, USA.
  • Singhal C; MD.AI, New York, NY, USA.
  • Zhou Q; MD.AI, New York, NY, USA.
  • Andriole KP; Mass General Brigham and Harvard Medical School, Boston, MA, USA.
  • Auffermann WF; University of Utah Health, Salt Lake City, UT, USA.
  • Prasanna PM; University of Utah Health, Salt Lake City, UT, USA.
  • Pham TX; University of Utah Health, Salt Lake City, UT, USA.
  • Peterson M; University of Utah Health, Salt Lake City, UT, USA.
  • Bergquist PJ; Medstar Georgetown University Hospital, Washington DC, USA.
  • Cook TS; University of Pennsylvania, Philadelphia, PA, USA.
  • Ferraciolli SF; DASA, Alphaville, Barueri, SP, Brazil.
  • Corradi GCA; DASA, Alphaville, Barueri, SP, Brazil.
  • Takahashi MS; DASA, Alphaville, Barueri, SP, Brazil.
  • Workman CS; Vanderbilt University Medical Center, Nashville TN, USA.
  • Parekh M; Department of Radiology, Thomas Jefferson University, Sidney Kimmel Jefferson Medical College, 111 S 11th St, Philadelphia, PA, 19107, USA.
  • Kamel SI; Department of Radiology, Thomas Jefferson University, Sidney Kimmel Jefferson Medical College, 111 S 11th St, Philadelphia, PA, 19107, USA.
  • Galant J; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Mas-Sanchez A; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Benítez EC; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Sánchez-Valverde M; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Jaques L; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Panadero M; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Vidal M; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Culiañez-Casas M; Hospital Universitario San Juan de Alicante, San Juan de Alicante, Alicante, Spain.
  • Angulo-Gonzalez D; Virgen del Rocio University Hospital, Seville, Spain.
  • Langer SG; Mayo Clinic, Rochester, MN, USA.
  • de la Iglesia-Vayá M; The Foundation for the Promotion of Health and Biomedical Research of Valencia Region, Valencia, Spain.
  • Shih G; Weill Cornell Medicine, New York, NY, USA.
J Digit Imaging ; 2022 Sep 28.
Article in English | MEDLINE | ID: covidwho-2267833
ABSTRACT
We describe the curation, annotation methodology, and characteristics of the dataset used in an artificial intelligence challenge for detection and localization of COVID-19 on chest radiographs. The chest radiographs were annotated by an international group of radiologists into four mutually exclusive categories, including "typical," "indeterminate," and "atypical appearance" for COVID-19, or "negative for pneumonia," adapted from previously published guidelines, and bounding boxes were placed on airspace opacities. This dataset and respective annotations are available to researchers for academic and noncommercial use.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal subject: Diagnostic Imaging / Medical Informatics / Radiology Year: 2022 Document Type: Article Affiliation country: S10278-022-00706-8

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal subject: Diagnostic Imaging / Medical Informatics / Radiology Year: 2022 Document Type: Article Affiliation country: S10278-022-00706-8