Deep Learning Algorithm for Traumatic Splenic Injury Detecti... | Clinical Trial | StuddyBuddy@endsection Deep Learning Algorithm for Traumatic Splenic Injury Detection and Sequential Localization
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Completed NCT05643612

Deep Learning Algorithm for Traumatic Splenic Injury Detection and Sequential Localization

Conditions: Spleen Injury, Machine Learning

Sex: All
Ages: 18 Years – N/A
Healthy volunteers: 1
Enrollment: 600
Sponsor: Chang Gung Memorial Hospital

Location: Taiwan

Summary

Spleen laceration is a lethal abdominal trauma and usually be diagnosed by medical images such as computed tomography. Deep learning had been proved its usage in detect abnormalities in medical images.In this trial, we used de-identified registry databank to develop a novel deep-learning based algorithm to detect the spleen trauma and to identify the injury locations.

Eligibility Criteria

Inclusion Criteria:patients who underwent abdominal computed tomography in emergency department for trauma and acute abdominal survey from Jul 2008 to Dec 2017.Exclusion Criteria:poor quality imagesno contrast series of computed tomography images.images from other hospitals without proper evaluation

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View on ClinicalTrials.gov

Source: ClinicalTrials.gov (NCT05643612). StuddyBuddy aggregates publicly available trial information.