The aim of this study is to use artificial intelligence in the form of machine learning analysing vital signs as well as symptoms of patients suffering from Covid19 to identify predictors of disease progression and severe course of disease.
Study Type
OBSERVATIONAL
Enrollment
1,000
Machine learning on vital parameters, clinical symptoms and underlying diseases
Quantification of the prediction power and identification of the most relevant predictive parameters
University Hospital of Tuebingen
Tübingen, Germany
RECRUITINGProbability of Participants for Hospitalisation or Fatal Outcome
Time frame: Detection of severe acute respiratory syndrome- Corona Virus 2 (SARS-CoV2) to recovery, hospitalisation or fatal outcome up to 5 weeks
Probability of Participants for Intensive Care Unit Admission
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Probability of Participants for Fatal Outcome
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Prediction of persisting health impairment by using standardized questionnaires
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Detection of symptoms, vital parameters and comorbidities predicting clinical course
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Influence of size of training data set
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Influence of viral load on the course of disease/ clinical outcome
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Influence of different virus variants on the course of disease/ clinical outcome
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Influence of SARS-CoV2 vaccination (yes/no) on the course of disease/ clinical outcome
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Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Evaluation of parameters (symptoms, vital parameters, comorbidities) according to their potential of clinical course predictions
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Probability of Participants for hospitalisation
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks
Influence of different SARS-CoV2 vaccines on the course of disease/ clinical outcome
Time frame: Detection of SARS-CoV2 to recovery, hospitalisation or fatal outcome up to 5 weeks