PMC:7782580 / 9852-11062 JSONTXT

{"target":"https://pubannotation.org/docs/sourcedb/PMC/sourceid/7782580","sourcedb":"PMC","sourceid":"7782580","source_url":"https://www.ncbi.nlm.nih.gov/pmc/7782580","text":"Multi-modal data from multiple sources were used in this study. X-data, CT-data, and clinical data used in our research were collected from four public data sets and one frontline hospital data (Youan hospital). Each data set was divided into two parts: train-val part and test part using a train-test-split function (TTSF) of the scikit-learn library which is shown in Table 1. The details of the multi-modal data types are described in the “Methods” section (see “Data sets splitting” section).\nTable 1 Number of cases from four public data sets and the Youan hospital (X-data, CT-data, clinical indicator data).\nStudy X-data CT-data Clinical data\nTrain + Val Test Train + Val Test Train + Val Test\n*Normal (RSNA + LUNA16) 5000 100 100 20 – –\nPneumonia (RSNA + ICNP) 3000 100 83 20 – –\nCOVID-19 (CCD) 150 62 – – – –\nInfluenza (Youan Hospital) 100 45 35 15 – –\n*Normal (Youan Hospital) 478 25 139 20 – –\nPneumonia (Youan Hospital) 380 55 180 35 – –\nCOVID-19 (Youan Hospital) 35 10 75 20 75 20\nTotal 9143 397 612 130 75 20\nThe term *Normal in this work means the cases where the lungs are not manifest evidence of COVID-19, influenza, or pneumonia on imaging and the RT-PCR testing of the COVID-19 is 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