Machine learning of neuroimaging to diagnose cognitive impairment and dementia: a systematic review and comparative analysis. - Enrico Pellegrini; Lucia Ballerini; Maria del C. Valdés Hernández; Francesca M. Chappell; Víctor González-Castro; Devasuda Anblagan; Samuel Danso; Susana Muñoz Maniega; Dominic Job; Cyril R. Pernet; Grant Mair; Tom J. MacGillivray; et al. (CoRR, 2018)

Text mining brain imaging reports. - Beatrice Alex; Claire Grover; Richard Tobin; Cathie Sudlow; Grant Mair; William Whiteley (J. Biomed. Semant., 2019)

A validated natural language processing algorithm for brain imaging phenotypes from radiology reports in UK electronic health records. - Emily Wheater; Grant Mair; Cathie Sudlow; Beatrice Alex; Claire Grover; William Whiteley (BMC Medical Informatics Decis. Mak., 2019)

A Comparison of Cranial Cavity Extraction Tools for Non-contrast Enhanced CT Scans in Acute Stroke Patients. - Laurence Vass; M. J. Moore; Taylor Hanayik; Grant Mair; S. T. Pendlebury; Nele Demeyere; Mark Jenkinson (Neuroinformatics, 2022)

ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. - Alessandro Fontanella; Antreas Antoniou; Wenwen Li 003; Joanna M. Wardlaw; Grant Mair; Emanuele Trucco; Amos J. Storkey (ICML, 2023)

Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images. - Alessandro Fontanella; Grant Mair; Joanna M. Wardlaw; Emanuele Trucco; Amos J. Storkey (CoRR, 2023)

Development of a Deep Learning Method to Identify Acute Ischemic Stroke Lesions on Brain CT. - Alessandro Fontanella; Wenwen Li 003; Grant Mair; Antreas Antoniou; Eleanor Platt; Paul A. Armitage; Emanuele Trucco; Joanna M. Wardlaw; Amos J. Storkey (CoRR, 2023)

Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports. - Arlene Casey; Emma M. Davidson; Claire Grover; Richard Tobin; Andreas Grivas; Huayu Zhang; Patrick Schrempf; Alison Q. O'Neil; Liam Lee; Michael Walsh; Freya Pellie; Karen Ferguson; et al. (Frontiers Digit. Health, 2023)

Pre-processing and Quality Control of Large Clinical CT Head Datasets for Intracranial Arterial Calcification Segmentation. - Benjamin Jin; Maria del C. Valdés Hernández; Alessandro Fontanella; Wenwen Li 003; Eleanor Platt; Paul A. Armitage; Amos J. Storkey; Joanna M. Wardlaw; Grant Mair (DEMI@MICCAI, 2024)

Deep learning biomarker of chronometric and biological ischemic stroke lesion age from unenhanced CT. - Adam Marcus 003; Grant Mair; Liang Chen 018; Charles Hallett; Claudia Ghezzou Cuervas-Mons; Dylan Roi; Daniel Rueckert; Paul Bentley (npj Digit. Medicine, 2024)

Calibrated Self-supervised Vision Transformers Improve Intracranial Arterial Calcification Segmentation from Clinical CT Head Scans. - Benjamin Jin; Grant Mair; Joanna M. Wardlaw; Maria del C. Valdés Hernández (CoRR, 2025)