Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study-MedSci.cn

Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

Orton, MR; Hann, E; Doran, SJ; Shepherd, STC; Ap Dafydd, D; Spencer, CE; López, JI; Albarrán-Artahona, V; Comito, F; Warren, H; Shur, J; Messiou, C; Larkin, J; Turajlic, S; Koh, DM

Koh, DM (通讯作者)，Royal Marsden NHS Fdn Trust, Artificial Intelligence Imaging Hub, London, England.;Koh, DM (通讯作者)，Inst Canc Res, Div Radiotherapy & Imaging, London, England.;Koh, DM (通讯作者)，Royal Marsden NHS Fdn Trust, Dept Radiol, London, England.

Abstract

BackgroundThe aim of this work is to evaluate the performance of radiomics predictions for a range of molecular, genomic and clinical targets in patie......

Full Text Link

Links

内科

外科

专科科室

热点

按科室浏览

临床工具

科研工具

其他工具

科研数智化

真实世界研究解决方案

数字化学术传播解决方案

其它

Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

科室

工具

服务