Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

• Main Authors: Asteris, Panagiotis G., Gavriilaki, Eleni, Touloumenidou, Tasoula, Koravou, Evaggelia-Evdoxia, Koutra, Maria, Papayanni, Penelope Georgia, Pouleres, Alexandros, Karali, Vassiliki, Lemonis, Minas E., Mamou, Anna, Skentou, Athanasia D., Papalexandri, Apostolia, Varelas, Christos, Chatzopoulou, Fani, Chatzidimitriou, Maria, Chatzidimitriou, Dimitrios, Veleni, Anastasia, Rapti, Evdoxia, Kioumis, Ioannis, Kaimakamis, Evaggelos, Bitzani, Milly, Boumpas, Dimitrios, Tsantes, Argyris, Sotiropoulos, Damianos, Papadopoulou, Anastasia, Kalantzis, Ioannis G., Vallianatou, Lydia A., Armaghani, Danial J., Cavaleri, Liborio, Gandomi, Amir H., Hajihassani, Mohsen, Hasanipanah, Mahdi, Koopialipoor, Mohammadreza, Lourenco, Paulo B., Samui, Pijush, Zhou, Jian, Sakellari, Ioanna, Valsami, Serena, Politou, Marianna, Kokoris, Styliani, Anagnostopoulos, Achilles
• Format: Article
• Published: Wiley 2022
• Subjects: QH301 Biology
• Online Access: http://eprints.um.edu.my/33463/
• Institution: Universiti Malaya

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) pre...