Remote Patient Monitoring and Detection of Possible Diseases With Artificial Intelligence Telemedicine System
AI - diseases
SETİNT AI-Diseases
1 other identifier
observational
1,000
1 country
1
Brief Summary
Remote patient monitoring and detection of possible diseases with Artificial Intelligence Telemedicine System
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Mar 2020
Typical duration for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
March 30, 2020
CompletedPrimary Completion
Last participant's last visit for primary outcome
July 20, 2021
CompletedFirst Submitted
Initial submission to the registry
February 3, 2022
CompletedFirst Posted
Study publicly available on registry
February 15, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
December 30, 2022
CompletedMarch 7, 2022
March 1, 2022
1.3 years
February 3, 2022
March 3, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Patient symptoms and disease confirmation
Her physician's patient symptom data were successfully matched to ICD-10 and other disease codes using the AI model.
May - October 2021
Study Arms (5)
fever
Remote patient monitoring. fever values recorded by the patient in the system. Validation of pre-diagnosis results of AI systems to detect fever-related diseases.
pulse
Remote patient monitoring. pulse values recorded by the patient in the system. Validation of pre-diagnosis results of AI systems to detect fever-related diseases.
blood pressure
Remote patient monitoring. Blood pressure values recorded by the patient in the system. Validation of pre-diagnosis results of AI systems to detect fever-related diseases.
oxygen saturation
Remote patient monitoring. oxygen saturationvalues recorded by the patient in the system. Validation of pre-diagnosis results of AI systems to detect fever-related diseases.
glucose
Remote patient monitoring. glucose values recorded by the patient in the system. Validation of pre-diagnosis results of AI systems to detect fever-related diseases.
Interventions
Possible diseases that may occur as a result of the patient's vital values with artificial intelligence systems
Eligibility Criteria
Patients registered in the SETINT AI artificial intelligence Telemedicine system
You may qualify if:
- No Eligibility Criteria
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Setint Ai
Düzce, 81620, Turkey (Türkiye)
Biospecimen
fever, pulse, blood pressure, oxygen saturation, glucose measurement values
Study Officials
- PRINCIPAL INVESTIGATOR
Aykut COŞKUN, MD
SETINT AI Robotic Sistem Eğitim ve Danışmanlık San.Tic.A.Ş.
- PRINCIPAL INVESTIGATOR
İsmail ÇELİK, MD
SETINT AI Robotic Sistem Eğitim ve Danışmanlık San.Tic.A.Ş.
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE CONTROL
- Time Perspective
- PROSPECTIVE
- Target Duration
- 9 Months
- Sponsor Type
- OTHER GOV
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Artificial Intelligence Specialist
Study Record Dates
First Submitted
February 3, 2022
First Posted
February 15, 2022
Study Start
March 30, 2020
Primary Completion
July 20, 2021
Study Completion
December 30, 2022
Last Updated
March 7, 2022
Record last verified: 2022-03