0000000000641587

AUTHOR

Styliani Kokoris

showing 2 related works from this author

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

2021

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) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, …

Male0304 Medicinal and Biomolecular Chemistry 0601 Biochemistry and Cell Biology 1103 Clinical SciencesBiochemistry & Molecular BiologyGreeceModels GeneticThrombomodulinCOVID-19Complement System ProteinsCell BiologyMiddle AgedPolymorphism Single NucleotideHospitalizationSettore ICAR/09 - Tecnica Delle CostruzioniIntensive Care UnitsComplement Factor HHumansMolecular MedicineFemaleNeural Networks ComputerMorbidityartificial intelligence complement complement inhibition COVID-19 genetic susceptibility SARS-CoV2Complement ActivationJournal of Cellular and Molecular Medicine
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Early prediction of COVID-19 outcome using artificial intelligence techniques and only five laboratory indices

2022

We aimed to develop a prediction model for intensive care unit (ICU) hospitalization of Coronavirus disease-19 (COVID-19) patients using artificial neural networks (ANN). We assessed 25 laboratory parameters at first from 248 consecutive adult COVID-19 patients for database creation, training, and development of ANN models. We developed a new alpha-index to assess association of each parameter with outcome. We used 166 records for training of computational simulations (training), 41 for documentation of computational simulations (validation), and 41 for reliability check of computational simulations (testing). The first five laboratory indices ranked by importance were Neutrophil-to-lymphoc…

Artificial intelligence Artificial neural networks COVID-19 Laboratory indices SARS-CoV2Settore ICAR/09 - Tecnica Delle CostruzioniImmunologyImmunology and Allergy
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