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O estudo clínico NCT07497243 para Chest X-ray for Clinical Evaluation está ainda não recrutando. Consulte a visualização em cartões do Radar de Estudos Clínicos e as ferramentas de descoberta de IA para ver todos os detalhes. Ou pergunte qualquer coisa aqui.
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X-ray Assisted Diagnostic System 16.000

Ainda não recrutando
Os detalhes do estudo clínico estão disponíveis principalmente em inglês. No entanto, a IA Trial Radar pode ajudar! Basta clicar em 'Explicar o estudo' para visualizar e discutir as informações do estudo no idioma selecionado.
O estudo clínico NCT07497243 é um estudo observacional para Chest X-ray for Clinical Evaluation. Seu status atual é: ainda não recrutando. O recrutamento está programado para iniciar em 1 de maio de 2026, com o objetivo de incluir 16.000 participantes. Coordenado por Union Hospital, Tongji Medical College, Huazhong University of Science and Technology e deve ser concluído em 30 de novembro de 2026. Essas informações foram atualizadas no ClinicalTrials.gov em 27 de março de 2026.
Resumo
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...Mostrar mais
Título oficial

Construction and Clinical Application of an X-ray AI-Aided Diagnosis System: A Randomized Controlled Trial

Condições médicas
Chest X-ray for Clinical Evaluation
Outros IDs do estudo
  • X-Ray-001
Número NCT
NCT07497243
Data de início (real)
2026-05-01
Última atualização postada
2026-03-27
Data de conclusão (estimada)
2026-11-30
Inscrição (estimada)
16.000
Tipo de estudo
Observacional
Status
Ainda não recrutando
Palavras-chave
X-Ray
AI
Chest diseases
Accuracy
Braços / Intervenções
Grupo de participantes/BraçoIntervenção/Tratamento
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.
Desfecho primário
Medida de desfechoDescrição da medidaPrazo
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
Desfecho secundário
Medida de desfechoDescrição da medidaPrazo
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
Assistente de participação
Critérios de elegibilidade

Idades elegíveis
Criança, Adulto, Idoso
Sexos elegíveis
Todos
Aceita voluntários saudáveis
Sim
  • 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 Technology logoUnion Hospital, Tongji Medical College, Huazhong University of Science and Technology
Contato central do estudo
Contato: Huangxuan Zhao, PhD, 18971676985, [email protected]
4 Locais do estudo em 1 países

Hubei

Wuhan Union Hospital, Wuhan, Hubei, 430022, China
Lei Chen, MD, Contato, 15971480677, [email protected]
Wuhan Union Jinyin Lake Hospital, Wuhan, Hubei, 430022, China
Lei Chen, Contato, 15971480677, [email protected]
Wuhan Union West Hospital, Wuhan, Hubei, 430022, China
Huangxuan Zhao, Contato, 18971676985, [email protected]
The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
Huangxuan Duan, Contato, 13209867189, [email protected]