Is Artificial Intelligence Replacing Our Radiology Stars? Not Yet!

European Urology Open Science(2023)

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摘要
Artificial intelligence (AI) is here to stay and will change health care as we know it. The availability of big data and the increasing numbers of AI algorithms approved by the US Food and Drug Administration together will help in improving the quality of care for patients and in overcoming human fatigue barriers. In oncology practice, patients and providers rely on the interpretation of radiologists when making clin-ical decisions; however, there is considerable variability among readers, and in par-ticular for prostate imaging. AI represents an emerging solution to this problem, for which it can provide a much-needed form of standardization. The diagnostic per-formance of AI alone in comparison to a combination of an AI framework and radi-ologist assessment for evaluation of prostate imaging has yet to be explored. Here, we compare the performance of radiologists alone versus a combination of radiol-ogists aided by a modern computer-aided diagnosis (CAD) AI system. We show that the radiologist-CAD combination demonstrates superior sensitivity and specificity in comparison to both radiologists alone and AI alone. Our findings demonstrate that a radiologist + AI combination could perform best for detection of prostate cancer lesions. A hybrid technology-human system could leverage the benefits of AI in improving radiologist performance while also reducing physician workload, minimizing burnout, and enhancing the quality of patient care. Patient summary: Our report demonstrates the potential of artificial intelligence (AI) for improving the interpretation of prostate scans. A combination of AI and evaluation by a radiologist has the best performance in determining the severity of prostate cancer. A hybrid system that uses both AI and radiologists could max-imize the quality of care for patients while reducing physician workload and burnout. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of European Association of Urology. This is an open access article under the CC BY-NC-ND license (http://creative-commons.org/licenses/by-nc-nd/4.0/).
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关键词
Artificial intelligence,Machine learning,Deep learning,Prostate cancer,Radiology,Performance,Radiomics,Multiparametric magnetic,resonance imaging
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