Early Diagnosis of Clinical Evolution From SARS-CoV-2

CORONABED.BOT: an Automation Project Using Artificial Intelligence for Early Diagnosis of Clinical Evolution From SARS-CoV-2

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05787405

Acronym

CORONABEDBOT

Enrollment

8000

Registered

2023-03-28

Start date

2020-12-01

Completion date

2024-01-10

Last updated

2025-03-12

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

SARS-CoV-1 Infection

Brief summary

The aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected with SARS-CoV-2. The objective of CORONABED.BOT is to analyze the care pathways of patients from the same cohort as CORONA.BOT, in order to identify the total length of stay, intensive care occupations and flows between departments, based on variables demographics and first entry clinics Early identification of patients with symptoms compatible with SARS-CoV-2 infection will enable more rapid activation of isolation procedures, contact monitoring/contact history and decisions on the most appropriate clinical pathway in terms of type of treatment and unit. Similarly, the identification of factors correlated with worse outcomes will allow more effective planning for the use of critical resources (such as intensive care and others).

Interventions

OTHERArtificial Intelligence methods

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Inclusion criteria

* adult patients (18 years of age or older) * admitted to the Gemelli and Columbus Polyclinic * diagnosis of SARS-CoV-2 infection (suspected cases will also be included).

Exclusion criteria

* aaaa

Design outcomes

Primary

Measure	Time frame	Description
the implementation of prediction models	24 months	tThe DataMart built will allow the creation of predictive models both for diagnosis of SARS-coV-2 pneumonia as well as death

Countries

Italy

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026