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NCT04661488

Safety and Reliability of Artificial Intelligence Driven Symptom Assessment in Children and Adolescentes

Status unknown Last updated 10 December 2020
What this trial tests

trial testing AI driven triage-system in Artificial Intelligence in 1,000 participants. Status unknown.

Timeline
1 December 2020
Primary endpoint
1 June 2021
1 December 2021

Quick facts

Lead sponsorTurku University Hospital
StatusStatus unknown
Study typeOBSERVATIONAL
Enrollment1,000
Start date1 December 2020
Primary completion1 June 2021
Estimated completion1 December 2021

Drugs / interventions tested

Conditions studied

Sponsor

Turku University Hospital

Who can join

Adults 0 to 17, any sex, with Artificial Intelligence or Triage. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Digital health technologies (DHT) are increasingly developed to support healthcare systems around the world. However, they are frequently lacking evidence-based medicine and medical validation. There is considerable need in the western countries to allocate healthcare resources accurately and give the population detailed and reliable health information enabling to take greater responsibility for their health. Intelligent patient flow management system (IPFM, product name Klinik Frontline) is developed to meet these needs. In practice, IPFM is used for decision support in the triaging and diagnostic processes as well as automatizing the management of inflow of the patients. The core of the IPFM is a clinical artificial intelligence (AI), which utilizes a comprehensive medical database of clinical correlations generated by medical doctors. The study population of this research consists of patients from the Paediatric Emergency Clinic of Turku University Hospital (TUH). Data will be gathered during 6 months of piloting, after which the results will be analysed. Anticipated number of patients to the study is minimum of 500 patients, with objective to be 1 000. When attending to the hospital, patients or their guardians will report their demographics, background information and symptoms using structured IPFM online form. Results obtained from IPFM are blinded from the healthcare professional and IPFM does not affect professional's clinical decision making. The data obtained from IPFM online form and clinical data from the emergency department and TUH will be analysed after the data collection. The main aim of the research is to validate the use of IPFM by evaluating the association of IPFM output with 1) urgency and severity of the conditions; and 2) actual diagnoses diagnosed by medical doctors. The main hypotheses of the research are that 1) IPFM is safe and sensitive in evaluating the urgency of the conditions of arriving patients at the emergency department and that 2) IPFM has sufficient correlation of differential diagnosis with actual diagnosis made by medical doctor.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Artificial Intelligence

Currently open trials in the same condition.

Other Turku University Hospital trials

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