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Breast Cancer Research : BCR|October 20, 2017
A novel and fully automated mammographic texture analysis for risk prediction: results from two case-control studiesChao Wang, Adam R Brentnall, Jack Cuzick, et al.
International Journal of Cancer|November 29, 2025
Indicators to identify cancer screening providers with suboptimal case detection: A scoping reviewJiayao Lei, Milena Falcaro, Adam R Brentnall, et al.
Breast Cancer Research : BCR|November 24, 2023
Development and evaluation of a method to assess breast cancer risk using a longitudinal history of mammographic density: a cohort studyEmma C Atakpa, Diana S M Buist, Erin J Aiello Bowles, et al.
Journal of Breast Imaging|August 20, 2019
A Case-Control Study to Add Volumetric or Clinical Mammographic Density into the Tyrer-Cuzick Breast Cancer Risk ModelAdam R Brentnall, Wendy F Cohn, William A Knaus, et al.
Cancer Biomarkers : Section a of Disease Markers|September 26, 2015
HPV33 DNA methylation measurement improves cervical pre-cancer risk estimation of an HPV16, HPV18, HPV31 and \textit{EPB41L3} methylation classifierAdam R Brentnall, Natasa Vasiljevic, Dorota Scibior-Bentkowska, et al.
NPJ Digital Medicine|November 28, 2023
An optimization framework to guide the choice of thresholds for risk-based cancer screeningAdam R Brentnall, Emma C Atakpa, Harry Hill, et al.
International Journal of Cancer|February 19, 2014
A DNA methylation classifier of cervical precancer based on human papillomavirus and human genesAdam R Brentnall, Nataša Vasiljević, Dorota Scibior-Bentkowska, et al.
International Journal of Cancer|May 17, 2017
Role of quantitative p16INK4A mRNA assay and digital reading of p16INK4A immunostained sections in diagnosis of cervical intraepithelial neoplasiaNataša Vasiljević, Paul D Carter, Caroline Reuter, et al.
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