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At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
Article Dans Une Revue Scientific Reports Année : 2024 At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods Domaines Origine Fichiers éditeurs autorisés sur une archive ouverte hal-04831133 , version 1 (10-03-2025) hal-04831133 , version 2 (10-06-2025) Munib Mesinovic, Xin Ci Wong, Giri Shan Rajahram, Barbara Wanjiru Citarella, Kalaiarasu Peariasamy, et al..
Modeling the relative influence of socio-demographic variables on post-acute COVID-19 quality of life: an application to settings in Europe, Asia, Africa, and South America
MS has received institutional research funds from the Johnson and Johnson foundation and from Janssen global public health. MS also received institutional research funding from Pfizer. TFM acknowledges support from NIH Training Grant 2T32AI007535. LFR was funded by Universidad de La Sabana (MED-309-2021). MS has been funded (in part) by contracts 200-2016-91779 and cooperative agreement CDC-RFA-FT-23-0069 with the Centers for Disease Control and Prevention (CDC).
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