Intracranial Hemorrhages
Conditions
Brief summary
cHS is a software that has been pre-learned based on a intracranial haemorrhage diagnosis model using brain CT images, and clinical decision support system for diagnosing intracranial haemorrhage by automatically analyzing brain CT images by assisting the medical team. The specific aims of this study are to evaluate efficacy of cHS for intracranial haemorrhage compared to the sensitivity and specificity levels of predicate device which is currently approved to triage intracranial haemorrhage.
Interventions
DEVICEcHS
Clinical decision support system for diagnosing intracranial haemorrhage
Sponsors
Heuron Inc.
Study design
Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
19 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults over 19 years old * Brain CT acquired * Abnormal cohort: A patient diagnosed with intracranial haemorrhage after a brain CT scan * Normal cohort: A normal person or a patient not diagnosed with intracranial haemorrhage after a brain CT scan
Exclusion criteria
* Patients with brain tumor or cerebral toxoplasmosis * Patients with brain abscess or brain calcification * Poor or incomplete brain CT image quality
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity and specificity of cHS | Within 4 weeks after collecting data | Sensitivity and specificity of cHS in diagnosis of intracranial haemorrhage based on golden standards |
Countries
South Korea
Outcome results
None listed