TY  - JOUR
AU  - Lakhani, Paras
AU  - Mongan, J
AU  - Singhal, C
AU  - Zhou, Q
AU  - Andriole, K P
AU  - Auffermann, W F
AU  - Prasanna, P M
AU  - Pham, T X
AU  - Peterson, Michael
AU  - Bergquist, P J
AU  - Cook, T S
AU  - Ferraciolli, S F
AU  - Corradi, G C A
AU  - Takahashi, M S
AU  - Workman, C S
AU  - Parekh, M
AU  - Kamel, S I
AU  - Galant, J
AU  - Mas-Sanchez, A
AU  - Benítez, E C
AU  - Sánchez-Valverde, M
AU  - Jaques, L
AU  - Panadero, M
AU  - Vidal, M
AU  - Culiañez-Casas, M
AU  - Angulo-Gonzalez, D
AU  - Langer, S G
AU  - de la Iglesia-Vayá, María
AU  - Shih, G
PY  - 2022
DO  - 10.1007/s10278-022-00706-8
UR  - http://hdl.handle.net/10668/20430
T2  - Journal of digital imaging
AB  - 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...
LA  - en
KW  - Artificial Intelligence
KW  - COVID-19
KW  - Machine Learning
KW  - Pneumonia
KW  - Radiography
KW  - Thorax
KW  - Humans
KW  - COVID-19
KW  - Artificial Intelligence
KW  - Radiography
KW  - Machine Learning
KW  - Radiologists
KW  - Radiography, Thoracic
TI  - The 2021 SIIM-FISABIO-RSNA Machine Learning COVID-19 Challenge: Annotation and Standard Exam Classification of COVID-19 Chest Radiographs.
TY  - research article
VL  - 36
ER  -