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An automated COVID-19 triage pipeline using artificial intelligence based on chest radiographs and clinical data.
Kim, Chris K; Choi, Ji Whae; Jiao, Zhicheng; Wang, Dongcui; Wu, Jing; Yi, Thomas Y; Halsey, Kasey C; Eweje, Feyisope; Tran, Thi My Linh; Liu, Chang; Wang, Robin; Sollee, John; Hsieh, Celina; Chang, Ken; Yang, Fang-Xue; Singh, Ritambhara; Ou, Jie-Lin; Huang, Raymond Y; Feng, Cai; Feldman, Michael D; Liu, Tao; Gong, Ji Sheng; Lu, Shaolei; Eickhoff, Carsten; Feng, Xue; Kamel, Ihab; Sebro, Ronnie; Atalay, Michael K; Healey, Terrance; Fan, Yong; Liao, Wei-Hua; Wang, Jianxin; Bai, Harrison X.
  • Kim CK; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Choi JW; Department of Computer Science, Brown University, Providence, RI, 02912, USA.
  • Jiao Z; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Wang D; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Wu J; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Yi TY; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Halsey KC; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Eweje F; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Tran TML; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Liu C; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Wang R; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Sollee J; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Hsieh C; Perelman School of Medicine at University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Chang K; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Yang FX; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Singh R; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Ou JL; Perelman School of Medicine at University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Huang RY; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Feng C; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Feldman MD; Department of Diagnostic Imaging, Rhode Island Hospital, Providence, RI, 02903, USA.
  • Liu T; Warren Alpert Medical School of Brown University, Providence, RI, 02912, USA.
  • Gong JS; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, 02129, USA.
  • Lu S; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Eickhoff C; Department of Computer Science, Brown University, Providence, RI, 02912, USA.
  • Feng X; Center for Computational Molecular Biology, Brown University, Providence, RI, 02912, USA.
  • Kamel I; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Sebro R; Department of Radiology, Brigham and Women's Hospital, Boston, MA, 02115, USA.
  • Atalay MK; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Healey T; Perelman School of Medicine at University of Pennsylvania, Philadelphia, PA, 19104, USA.
  • Fan Y; Department of Biostatistics, Brown University, Providence, RI, 02912, USA.
  • Liao WH; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Wang J; Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
  • Bai HX; Center for Biomedical Informatics, Brown University, Providence, RI, 02912, USA.
NPJ Digit Med ; 5(1): 5, 2022 Jan 14.
Article in English | MEDLINE | ID: covidwho-1625359
ABSTRACT
While COVID-19 diagnosis and prognosis artificial intelligence models exist, very few can be implemented for practical use given their high risk of bias. We aimed to develop a diagnosis model that addresses notable shortcomings of prior studies, integrating it into a fully automated triage pipeline that examines chest radiographs for the presence, severity, and progression of COVID-19 pneumonia. Scans were collected using the DICOM Image Analysis and Archive, a system that communicates with a hospital's image repository. The authors collected over 6,500 non-public chest X-rays comprising diverse COVID-19 severities, along with radiology reports and RT-PCR data. The authors provisioned one internally held-out and two external test sets to assess model generalizability and compare performance to traditional radiologist interpretation. The pipeline was evaluated on a prospective cohort of 80 radiographs, reporting a 95% diagnostic accuracy. The study mitigates bias in AI model development and demonstrates the value of an end-to-end COVID-19 triage platform.

Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Language: English Journal: NPJ Digit Med Year: 2022 Document Type: Article Affiliation country: S41746-021-00546-w

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Language: English Journal: NPJ Digit Med Year: 2022 Document Type: Article Affiliation country: S41746-021-00546-w