Urinary volatile organic compounds (VOCs) based prostate cancer diagnosis via high-dimensional classification

IF 1.2 4区数学 Q2 STATISTICS & PROBABILITY

Journal of Applied Statistics Pub Date : 2024-04-26 DOI:10.1080/02664763.2024.2346355

George Ekow Quaye, Wen-Yee Lee, Elizabeth Noriega Landa, Sabur Badmos, Kiana L. Holbrook, Xiaogang Su

引用次数: 0

Abstract

Early detection of prostate cancer is critical for successful treatment and survival. However, current diagnostic methods such as prostate-specific antigen (PSA) testing and digital rectal examinat...

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基于尿液挥发性有机化合物 (VOC) 的前列腺癌诊断高维分类法

前列腺癌的早期发现对于成功治疗和生存至关重要。然而，目前的诊断方法，如前列腺特异性抗原（PSA）检测和数字直肠镜检查，对前列腺癌的早期诊断并不有效。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Applied Statistics 数学-统计学与概率论

CiteScore

3.40

自引率

0.00%

发文量

126

审稿时长

6 months

期刊介绍： Journal of Applied Statistics provides a forum for communication between both applied statisticians and users of applied statistical techniques across a wide range of disciplines. These areas include business, computing, economics, ecology, education, management, medicine, operational research and sociology, but papers from other areas are also considered. The editorial policy is to publish rigorous but clear and accessible papers on applied techniques. Purely theoretical papers are avoided but those on theoretical developments which clearly demonstrate significant applied potential are welcomed. Each paper is submitted to at least two independent referees.