Trial Radar KI | ||
|---|---|---|
Die klinische Studie NCT07497243 für Chest X-ray for Clinical Evaluation ist noch nicht rekrutierend. In der Kartenansicht des Klinische Studien Radar und den KI-Entdeckungstools finden Sie alle Details. Oder stellen Sie hier Ihre Fragen. | ||
Eine Studie entspricht den Filterkriterien
Kartenansicht
X-ray Assisted Diagnostic System 16.000
Die Details der klinischen Studie sind hauptsächlich auf Englisch verfügbar. Trial Radar KI kann jedoch helfen! Klicken Sie einfach auf 'Studie erklären', um die Informationen zur Studie in der ausgewählten Sprache anzuzeigen und zu besprechen.
Die klinische Studie NCT07497243 ist eine beobachtungsstudie zur Untersuchung von Chest X-ray for Clinical Evaluation und hat den Status noch nicht rekrutierend. Der Start ist für 1. Mai 2026 geplant, bis 16.000 Teilnehmer aufgenommen werden. Durchgeführt von Union Hospital, Tongji Medical College, Huazhong University of Science and Technology wird der Abschluss für 30. November 2026 erwartet. Die Daten von ClinicalTrials.gov wurden zuletzt am 27. März 2026 aktualisiert.
Kurzbeschreibung
X-ray examination is one of the most commonly used imaging modalities, especially chest X-ray, which is routinely performed for hospitalized patients. However, due to the low density resolution of X-ray images, radiologists' ability to diagnose diseases-particularly small lesions-is often affected. Studies have shown that the diagnostic accuracy of radiologists using chest X-rays is only around 70%, which does not me...Mehr anzeigen
Offizieller Titel
Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial
Erkrankungen
Chest X-ray for Clinical EvaluationWeitere Studien-IDs
- X-Ray-001
NCT-Nummer
Studienbeginn (tatsächlich)
2026-05-01
Zuletzt aktualisiert
2026-03-27
Studienende (vorauss.)
2026-11-30
Geplante Rekrutierung
16.000
Studientyp
Beobachtungsstudie
Status
Noch nicht rekrutierend
Stichwörter
X-Ray
AI
Chest diseases
Accuracy
AI
Chest diseases
Accuracy
Studienarme/Interventionen
| Teilnehmergruppe/Studienarm | Intervention/Behandlung |
|---|---|
Radiologist diagnostic group After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis. | Radiologist diagnostic group After the patient undergoes an X-ray examination, a radiologist generates the report and makes the diagnosis. |
AI-assisted radiologist diagnostic group After the patient undergoes an X-ray examination, an AI-assisted radiologist generates the report and makes the diagnosis. | AI-assisted radiologist diagnostic group Based on the previously developed X-ray image diagnosis and report generation model, radiologists are assisted in interpreting X-ray images and generating reports. |
Hauptergebnismessungen
Nebenergebnismessungen
| Ergebnismessung | Beschreibung der Messung | Zeitrahmen |
|---|---|---|
Area Under the Curve | The primary outcome was the AUC to evaluate diagnostic performance, comparing radiologists with and without AI assistance. | From enrollment to the end of X-ray image acquisition at 1 week |
| Ergebnismessung | Beschreibung der Messung | Zeitrahmen |
|---|---|---|
X-ray report generation time | X-ray report generation time refers to the amount of time required to produce a diagnostic report after an X-ray examination has been performed. It typically measures the interval from when the X-ray images are acquired to when the radiologist (with or without AI assistance) completes and finalizes the report. | From enrollment to the end of X-ray image acquisition at 1 week |
Teilnahme-Assistent
Eignungskriterien
Zugelassene Altersgruppen
Kind, Erwachsene, Ältere Erwachsene
Zugelassene Geschlechter
Alle
Akzeptiert gesunde Freiwillige
Ja
- Clinically suspected thoracic diseases (such as pneumonia, tuberculosis, or lung cancer) requiring X-ray diagnosis；
- Patients providing written informed consent for research data use；
- Complete clinical records (including chief complaints, medical history, and laboratory test results)
- Substandard X-ray image quality (including severe motion artifacts, over-/underexposure, or missing anatomical structures)
- Pregnant or lactating women
Union Hospital, Tongji Medical College, Huazhong University of Science and TechnologyZentrale Studienkontakte
Kontakt: Huangxuan Zhao, PhD, 18971676985, [email protected]
4 Studienstandorte in 1 Ländern
Hubei
Wuhan Union Hospital, Wuhan, Hubei, 430022, China
Lei Chen, MD, Kontakt, 15971480677, [email protected]
Wuhan Union Jinyin Lake Hospital, Wuhan, Hubei, 430022, China
Lei Chen, Kontakt, 15971480677, [email protected]
Wuhan Union West Hospital, Wuhan, Hubei, 430022, China
Huangxuan Zhao, Kontakt, 18971676985, [email protected]
The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
Huangxuan Duan, Kontakt, 13209867189, [email protected]