Improving Prostate Cancer Risk Prediction through Partial AUC Optimization-Reference-Cited by-同舟云学术

Improving Prostate Cancer Risk Prediction through Partial AUC Optimization

Published:2024-05-13 Issue: Volume:22 Page:1170-1173
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Container-title:Companion Proceedings of the ACM Web Conference 2024
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Author:

Zhu Xinyuan¹^ORCID,Ren Xiaohan²^ORCID,Shi Wentao¹^ORCID,Wang Changming³^ORCID,Liu Xuehan⁴^ORCID,Liu Yuqing⁵^ORCID,Tao Tao³^ORCID,Feng Fuli¹^ORCID

Affiliation:

1. School of Information Science and Technology, University of Science and Technology of China, Hefei, China

2. School of the Gifted Young, University of Science and Technology of China, Hefei, China

3. Department of Urology, The First Affiliated Hospital of USTC, Hefei, China

4. Core Facility Center for Medical Sciences, The First Affiliated Hospital of USTC, Hefei, China

5. Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China

Funder

University Synergy Innovation Program of Anhui Province

the Key Direction of New Medicine Fund of USTC

the Key Research and Development Project of Anhui Province

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589335.3651458

Reference13 articles.

1. Reducing Prostate Cancer Overdiagnosis

2. Prostate cancer risk prediction models in Eastern Asian populations: current status, racial difference, and future directions;He Biming;Asian Journal of Andrology,2019

3. Hua Ma, Andriy I. Bandos, Howard E. Rockette, and David Gur. 2013. On use of partial area under the ROC curve for evaluation of diagnostic performance. Statistics in Medicine , Vol. 32 (2013). https://api.semanticscholar.org/CorpusID:206484909

4. Analyzing a Portion of the ROC Curve

5. A Magnetic Resonance Imaging–Based Prediction Model for Prostate Biopsy Risk Stratification