Radiograph accelerated detection and identification of cancer in the lung (RADICAL): a mixed methods study to assess the clinical effectiveness and acceptability of Qure.ai artificial intelligence software to prioritise chest X-ray (CXR) interpretation.

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第一作者： Sean F,Duncan

第一单位： Digital Health Validation Lab, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK.

作者： Sean F,Duncan ^[1] ; Alex,McConnachie ^[2] ; James,Blackwood ^[3] ; David B,Stobo ^[4] ; John D,Maclay ^[5] ; O,Wu ^[6] ; Evi,Germeni ^[6] ; Dennis,Robert ^[7] ; Banu,Bilgili ^[7] ; Shamie,Kumar ^[7] ; Mark,Hall ^[4] ; David J,Lowe ^[8]

作者单位： Digital Health Validation Lab, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK. ^[1] Robertson Centre for Biostatistics, University of Glasgow, Glasgow, UK. ^[2] NHS Greater Glasgow and Clyde, Glasgow, UK. ^[3] Radiology, Queen Elizabeth University Hospital, Glasgow, UK. ^[4] Respiratory Medicine, Glasgow Royal Infirmary, Glasgow, UK.;School of Medicine, Dentistry & Nursing, University of Glasgow, Glasgow, UK. ^[5] Health Economics and Health Technology Assessment (HEHTA), University of Glasgow, Glasgow, UK. ^[6] Qure.AI, Mumbai, India. ^[7] Digital Health Validation Lab, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, UK David.lowe@glasgow.ac.uk.;Emergency Department, Queen Elizabeth University Hospital Campus, Glasgow, UK. ^[8]

关键词 Adult thoracic medicine Chest imaging Diagnostic Imaging Health economics Respiratory tract tumours