PSA-based machine learning model improves prostate cancer risk stratification in a screening population

被引:0
作者
Marlon Perera
Rohan Mirchandani
Nathan Papa
Geoff Breemer
Anna Effeindzourou
Lewis Smith
Peter Swindle
Elliot Smith
机构
[1] Mater Hospital,Department of Urology
[2] Austin Health,Department of Surgery
[3] The University of Melbourne,Faculty of Medicine
[4] University of Queensland,School of Public Health and Preventive Medicine
[5] Monash University,undefined
[6] Maxwell Plus,undefined
来源
World Journal of Urology | 2021年 / 39卷
关键词
Prostate cancer; Prostate-specific membrane antigen; Prostate cancer screening; Machine learning; Artificial intelligence;
D O I
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中图分类号
学科分类号
摘要
引用
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页码:1897 / 1902
页数:5
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共 81 条
[21]  
Emberton M(2007)Initial biopsy outcome prediction–head-to-head comparison of a logistic regression-based nomogram versus artificial neural network Eur Urol. 51 1236-1240
[22]  
Moore CM(2019)Machine learning applications in prostate cancer magnetic resonance imaging Eur Radiol Exp 7 35-527
[23]  
Ito K(2019)Prostate cancer detection using deep convolutional neural networks Sci Rep 20 19518-417
[24]  
Yamamoto T(2018)(68)Ga-prostate specific membrane antigen (PSMA) positron emission tomography (PET) for primary staging of high-risk prostate cancer: a systematic review World J Urol 36 519-undefined
[25]  
Ohi M(2020)Gallium-68 prostate-specific membrane antigen positron emission tomography in advanced prostate cancer-updated diagnostic utility, sensitivity, specificity, and distribution of prostate-specific membrane antigen-avid lesions: a systematic review and meta-analysis Eur Urol 77 403-undefined
[26]  
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[27]  
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[28]  
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[29]  
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[30]  
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