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A comprehensive AI model development framework for consistent Gleason grading.

Xinmi HuoKok Haur OngKah Weng LauLaurent GoleDavid M YoungChar Loo TanXiaohui ZhuChongchong ZhangYonghui ZhangLongjie LiHao HanHaoda LuJing ZhangJun HouHuanfen ZhaoHualei GanLijuan YinXingxing WangXiaoyue ChenHong LvHaotian CaoXiaozhen YuYabin ShiZiling HuangGabriel MariniJun XuBingxian LiuBingxian ChenQiang WangKun GuiWenzhao ShiYingying SunWanyuan ChenDalong CaoStephan J SandersHwee Kuan LeeSusan Swee Shan HueWeimiao YuSoo Yong Tan
Published in: Communications medicine (2024)
This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.
Keyphrases
  • prostate cancer
  • artificial intelligence
  • radical prostatectomy
  • magnetic resonance imaging
  • magnetic resonance
  • machine learning
  • deep learning